Silabus Mata Kuliah Jaringan Syaraf Tiruan

a.    Sejarah JST, model JST, fungsi aktivasi, prinsip dasar pelatihan JST

b.   Arsitektur dan algoritma  Jaringan syaraf sederhana (McCulloch-Pitt, hebb, perceptron, adaline, madaline)

Jaringan syaraf assosiative

a.     Algoritma Training untuk pattern association

b.    Heteroassociative memory

c.    Autoassociative

d.    Bidirectional associative memory (BAM)

Jaringan syaraf Competitive

a.     Fixed weight competitive (maxnet, mexican, hamming)

b.    Kohonen self – organizing maps

c.     Learning vector quantization (LVQ)

Backpropagation

Backpropagation standard, arsitektur, algoritma dan aplikasinya

Aplikasi jaringan syaraf tiruan diberbagai bidang:  pengenalan pola, peramalan, dll

Fausett, Laurene,1994,. Fundamentals of Neural Networks, Prentice-Hall  International, Inc.,USA

Pustaka Pendukung

1.       Demuth, Howard and Mark Belle, Neural Network Toolbox : for use with MATLAB, (online available), Mathworks, 2002

2.       Li Min Fu, 1994, Neural Networks in Computer Intelligence, McGraw-Hill International, New York.

3.       Neural Networks for Pattern Recognition, The MIT Press, Cambridge, MA

4.       Rao, Valluru B. dan Rao, Hayagriva V, 1993, C++ Neural Networks and Fuzzy Logic,  MIS Press, New York