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12.815 Atmospheric Radiation (MIT) 12.815 Atmospheric Radiation (MIT)

Description

This is an introduction to the physics of atmospheric radiation and remote sensing including use of computer codes. Subjects covered include: radiative transfer equation including emission and scattering, spectroscopy, Mie theory, and numerical solutions. We examine the solution of inverse problems in remote sensing of atmospheric temperature and composition. This is an introduction to the physics of atmospheric radiation and remote sensing including use of computer codes. Subjects covered include: radiative transfer equation including emission and scattering, spectroscopy, Mie theory, and numerical solutions. We examine the solution of inverse problems in remote sensing of atmospheric temperature and composition.Subjects

atmospheric radiation | atmospheric radiation | remote sensing | remote sensing | atmospheric physics | atmospheric physics | computer codes | computer codes | Radiative transfer equation | Radiative transfer equation | emission and scattering | emission and scattering | spectroscopy | spectroscopy | Mie theory | Mie theory | numerical solutions | numerical solutions | inverse problems | inverse problems | atmospheric temperature | atmospheric temperature | atmospheric composition | atmospheric compositionLicense

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 metadata2.717J Optical Engineering (MIT) 2.717J Optical Engineering (MIT)

Description

This course concerns the theory and practice of optical methods in engineering and system design, with an emphasis on diffraction, statistical optics, holography, and imaging. It provides the engineering methodology skills necessary to incorporate optical components in systems serving diverse areas such as precision engineering and metrology, bio-imaging, and computing (sensors, data storage, communication in multi-processor systems). Experimental demonstrations and a design project are included. This course concerns the theory and practice of optical methods in engineering and system design, with an emphasis on diffraction, statistical optics, holography, and imaging. It provides the engineering methodology skills necessary to incorporate optical components in systems serving diverse areas such as precision engineering and metrology, bio-imaging, and computing (sensors, data storage, communication in multi-processor systems). Experimental demonstrations and a design project are included.Subjects

optical methods in engineering and system design | optical methods in engineering and system design | diffraction | statistical optics | holography | and imaging | diffraction | statistical optics | holography | and imaging | Statistical Optics | Inverse Problems (i.e. theory of imaging) | Statistical Optics | Inverse Problems (i.e. theory of imaging) | applications in precision engineering and metrology | bio-imaging | and computing (sensors | data storage | communication in multi-processor systems) | applications in precision engineering and metrology | bio-imaging | and computing (sensors | data storage | communication in multi-processor systems) | Fourier optics | Fourier optics | probability | probability | stochastic processes | stochastic processes | light statistics | light statistics | theory of light coherence | theory of light coherence | van Cittert-Zernicke Theorem | van Cittert-Zernicke Theorem | statistical optics applications | statistical optics applications | inverse problems | inverse problems | information-theoretic views | information-theoretic views | information theory | information theory | 2.717 | 2.717 | MAS.857 | MAS.857License

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 metadata12.815 Atmospheric Radiation (MIT) 12.815 Atmospheric Radiation (MIT)

Description

This is an introduction to the physics of atmospheric radiation and remote sensing including use of computer codes. Subjects covered include: radiative transfer equation including emission and scattering, spectroscopy, Mie theory, and numerical solutions. We examine the solution of inverse problems in remote sensing of atmospheric temperature and composition. This is an introduction to the physics of atmospheric radiation and remote sensing including use of computer codes. Subjects covered include: radiative transfer equation including emission and scattering, spectroscopy, Mie theory, and numerical solutions. We examine the solution of inverse problems in remote sensing of atmospheric temperature and composition.Subjects

atmospheric radiation | atmospheric radiation | remote sensing | remote sensing | atmospheric physics | atmospheric physics | computer codes | computer codes | Radiative transfer equation | Radiative transfer equation | emission and scattering | emission and scattering | spectroscopy | spectroscopy | Mie theory | Mie theory | numerical solutions | numerical solutions | inverse problems | inverse problems | atmospheric temperature | atmospheric temperature | atmospheric composition | atmospheric compositionLicense

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 metadata12.815 Atmospheric Radiation (MIT) 12.815 Atmospheric Radiation (MIT)

Description

This is an introduction to the physics of atmospheric radiation and remote sensing including use of computer codes. Subjects covered include: radiative transfer equation including emission and scattering, spectroscopy, Mie theory, and numerical solutions. We examine the solution of inverse problems in remote sensing of atmospheric temperature and composition. This is an introduction to the physics of atmospheric radiation and remote sensing including use of computer codes. Subjects covered include: radiative transfer equation including emission and scattering, spectroscopy, Mie theory, and numerical solutions. We examine the solution of inverse problems in remote sensing of atmospheric temperature and composition.Subjects

atmospheric radiation | atmospheric radiation | remote sensing | remote sensing | atmospheric physics | atmospheric physics | computer codes | computer codes | Radiative transfer equation | Radiative transfer equation | emission and scattering | emission and scattering | spectroscopy | spectroscopy | Mie theory | Mie theory | numerical solutions | numerical solutions | inverse problems | inverse problems | atmospheric temperature | atmospheric temperature | atmospheric composition | atmospheric compositionLicense

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 metadataDescription

This is a mostly self-contained research-oriented course designed for undergraduate students (but also extremely welcoming to graduate students) with an interest in doing research in theoretical aspects of algorithms that aim to extract information from data. These often lie in overlaps of two or more of the following: Mathematics, Applied Mathematics, Computer Science, Electrical Engineering, Statistics, and / or Operations Research. This is a mostly self-contained research-oriented course designed for undergraduate students (but also extremely welcoming to graduate students) with an interest in doing research in theoretical aspects of algorithms that aim to extract information from data. These often lie in overlaps of two or more of the following: Mathematics, Applied Mathematics, Computer Science, Electrical Engineering, Statistics, and / or Operations Research.Subjects

Principal Component Analysis (PCA) | Principal Component Analysis (PCA) | random matrix theory | random matrix theory | spike model | spike model | manifold learning | manifold learning | Diffusion Maps | Diffusion Maps | Sobolev Embedding Theorem | Sobolev Embedding Theorem | Spectral Clustering | Spectral Clustering | Cheeger’s inequality | Cheeger’s inequality | Mesh Theorem | Mesh Theorem | Number Theory | Number Theory | Approximation algorithms | Approximation algorithms | Max-Cut problem | Max-Cut problem | Stochastic Block Model | Stochastic Block Model | Synchronization | Synchronization | inverse problems | inverse problemsLicense

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 metadata2.717J Optical Engineering (MIT)

Description

This course concerns the theory and practice of optical methods in engineering and system design, with an emphasis on diffraction, statistical optics, holography, and imaging. It provides the engineering methodology skills necessary to incorporate optical components in systems serving diverse areas such as precision engineering and metrology, bio-imaging, and computing (sensors, data storage, communication in multi-processor systems). Experimental demonstrations and a design project are included.Subjects

optical methods in engineering and system design | diffraction | statistical optics | holography | and imaging | Statistical Optics | Inverse Problems (i.e. theory of imaging) | applications in precision engineering and metrology | bio-imaging | and computing (sensors | data storage | communication in multi-processor systems) | Fourier optics | probability | stochastic processes | light statistics | theory of light coherence | van Cittert-Zernicke Theorem | statistical optics applications | inverse problems | information-theoretic views | information theory | 2.717 | MAS.857License

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 metadata12.815 Atmospheric Radiation (MIT)

Description

This is an introduction to the physics of atmospheric radiation and remote sensing including use of computer codes. Subjects covered include: radiative transfer equation including emission and scattering, spectroscopy, Mie theory, and numerical solutions. We examine the solution of inverse problems in remote sensing of atmospheric temperature and composition.Subjects

atmospheric radiation | remote sensing | atmospheric physics | computer codes | Radiative transfer equation | emission and scattering | spectroscopy | Mie theory | numerical solutions | inverse problems | atmospheric temperature | atmospheric compositionLicense

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 metadata2.717J Optical Engineering (MIT)

Description

This course concerns the theory and practice of optical methods in engineering and system design, with an emphasis on diffraction, statistical optics, holography, and imaging. It provides the engineering methodology skills necessary to incorporate optical components in systems serving diverse areas such as precision engineering and metrology, bio-imaging, and computing (sensors, data storage, communication in multi-processor systems). Experimental demonstrations and a design project are included.Subjects

optical methods in engineering and system design | diffraction | statistical optics | holography | and imaging | Statistical Optics | Inverse Problems (i.e. theory of imaging) | applications in precision engineering and metrology | bio-imaging | and computing (sensors | data storage | communication in multi-processor systems) | Fourier optics | probability | stochastic processes | light statistics | theory of light coherence | van Cittert-Zernicke Theorem | statistical optics applications | inverse problems | information-theoretic views | information theory | 2.717 | MAS.857License

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 metadata18.S096 Topics in Mathematics of Data Science (MIT)

Description

This is a mostly self-contained research-oriented course designed for undergraduate students (but also extremely welcoming to graduate students) with an interest in doing research in theoretical aspects of algorithms that aim to extract information from data. These often lie in overlaps of two or more of the following: Mathematics, Applied Mathematics, Computer Science, Electrical Engineering, Statistics, and / or Operations Research.Subjects

Principal Component Analysis (PCA) | random matrix theory | spike model | manifold learning | Diffusion Maps | Sobolev Embedding Theorem | Spectral Clustering | ?s inequality | Mesh Theorem | Number Theory | Approximation algorithms | Max-Cut problem | Stochastic Block Model | Synchronization | inverse problemsLicense

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

https://ocw.mit.edu/rss/all/mit-allcourses.xmlAttribution

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See all metadata12.815 Atmospheric Radiation (MIT)

Description

This is an introduction to the physics of atmospheric radiation and remote sensing including use of computer codes. Subjects covered include: radiative transfer equation including emission and scattering, spectroscopy, Mie theory, and numerical solutions. We examine the solution of inverse problems in remote sensing of atmospheric temperature and composition.Subjects

atmospheric radiation | remote sensing | atmospheric physics | computer codes | Radiative transfer equation | emission and scattering | spectroscopy | Mie theory | numerical solutions | inverse problems | atmospheric temperature | atmospheric compositionLicense

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

https://ocw.mit.edu/rss/all/mit-allcourses.xmlAttribution

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

See all metadata12.815 Atmospheric Radiation (MIT)

Description

This is an introduction to the physics of atmospheric radiation and remote sensing including use of computer codes. Subjects covered include: radiative transfer equation including emission and scattering, spectroscopy, Mie theory, and numerical solutions. We examine the solution of inverse problems in remote sensing of atmospheric temperature and composition.Subjects

atmospheric radiation | remote sensing | atmospheric physics | computer codes | Radiative transfer equation | emission and scattering | spectroscopy | Mie theory | numerical solutions | inverse problems | atmospheric temperature | atmospheric compositionLicense

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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