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6.341 Discrete-Time Signal Processing (MIT) 6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semest This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semestSubjects

discrete time signals and systems | discrete time signals and systems | discrete-time processing of continuous-time signals | discrete-time processing of continuous-time signals | decimation | decimation | interpolation | interpolation | sampling rate conversion | sampling rate conversion | Flowgraph structures | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | linear prediction | Discrete Fourier transform | Discrete Fourier transform | FFT algorithm | FFT algorithm | Short-time Fourier analysis and filter banks | Short-time Fourier analysis and filter banks | Multirate techniques | Multirate techniques | Hilbert transforms | Hilbert transforms | Cepstral analysis | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semestSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semestSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata6.341 Discrete-Time Signal Processing (MIT)

Description

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications. Acknowledgements I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesSubjects

discrete time signals and systems | discrete-time processing of continuous-time signals | decimation | interpolation | sampling rate conversion | Flowgraph structures | time- and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters | linear prediction | Discrete Fourier transform | FFT algorithm | Short-time Fourier analysis and filter banks | Multirate techniques | Hilbert transforms | Cepstral analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata