A New Supervised Learning Algorithm for Multilayered and Interconnected Neural Networks  

Oleh:

Yamamoto, Y. ; Nikiforuk, P. N.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 11 no. 1 (2000), page 36-46.
Topik: multilayer networks; learning algorithm; multilayered; neural networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

A learning algorithm is presented for supervised learning of multilayered and interconnected neural networks without using a gradient method. First, fictitious teacher signals for the outputs of each hidden unit are algebraically determined by an error backpropagation (EBP) method. Then, the weight parameters are determined by using an exponentially weighted least squares (EWLS) method. This is called the EBP - EWLS algorithm for a multilayered neural network. For an interconnected neural network, the mathematical description of the neural network is arranged in the form for which the EBP - EWLS algorithm can be applied. Simulation studies have verified the proposed technique.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali