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Title : 9.641J Introduction to Neural Networks (MIT)

Title : 9.641J Introduction to Neural Networks (MIT)

Description : Organization of synaptic connectivity as the basis of neural computation and learning. Single and multilayer perceptrons. Dynamical theories of recurrent networks: amplifiers, attractors, and hybrid computation. Backpropagation and Hebbian learning. Models of perception, motor control, memory, and neural development.

Description : Organization of synaptic connectivity as the basis of neural computation and learning. Single and multilayer perceptrons. Dynamical theories of recurrent networks: amplifiers, attractors, and hybrid computation. Backpropagation and Hebbian learning. Models of perception, motor control, memory, and neural development.

Fromsemester : Fall

Fromsemester : Fall

Fromyear : 2002

Fromyear : 2002

Creator :

Creator :

Date : 2007-02-22T22:24:22+05:00

Date : 2007-02-22T22:24:22+05:00

Relation : 9.641J

Relation : 9.641J

Relation : 8.594J

Relation : 8.594J

Language : en-US

Language : en-US

Subject : synaptic connectivity

Subject : synaptic connectivity

Subject : computation

Subject : computation

Subject : learning

Subject : learning

Subject : multilayer perceptrons

Subject : multilayer perceptrons

Subject : recurrent networks

Subject : recurrent networks

Subject : amplifiers

Subject : amplifiers

Subject : attractors

Subject : attractors

Subject : hybrid computation

Subject : hybrid computation

Subject : Backpropagation

Subject : Backpropagation

Subject : Hebbian learning

Subject : Hebbian learning

Subject : perception

Subject : perception

Subject : motor control

Subject : motor control

Subject : memory

Subject : memory

Subject : neural development

Subject : neural development

Subject : 9.641

Subject : 9.641

Subject : 8.594

Subject : 8.594