Implementations of Artificial Neural Networks Using Current-Mode Pulse Width Modulation Techniques  

Oleh:

El-Masry, E. I. ; Yakout, M. A. ; Yang, H.-K.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 8 no. 3 (1997), page 532-548.
Topik: modulation; artificial; neural network; current - mode pulse; modulation techniques

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

The use of a current - mode pulse width modulation (CM - PWM) technique to implement analog artificial neural networks (ANN s) is presented. This technique can be used to efficiently implement the weighted summation operation (WSO) that are required in the realization of a general ANN. The sigmoidal transformation is inherently performed by the nonlinear transconductance amplifier, which is a key component in the current integrator used in the realization of WSO. The CM - PWM implementation results in a minimum silicon area, and therefore is suitable for very large scale neural systems. Other pronounced features of the CM - PWM implementation are its easy programmability, electronically adjustable gains of neurons, and modular structures. In this paper, all the current - mode CMOS circuits (building blocks) required for the realization of CM - PWM ANN s are presented and simulated. Four modules for modular design of ANN s are introduced. Also, it is shown that the CM -PWM technique is an efficient method for implementing discrete - time cellular neural networks (DT - CNN s). Two application examples are given : a winner - take - all circuit and a connected component detector.

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