This study introduces a methodology tailored to analog hardware architecture for
implementing an artificial neural network. The fundamental components of the architecture …

Fuzzy and Neuro-Fuzzy Systems in Medicineprovides a thorough review of state-of-the-art
techniques and practices, defines and explains relevant problems, as well as provides …

The aim of this paper is to propose a new classification approach of artificial neural networks
hardware. Our motivation behind this work is justified by the following two arguments: first …

This paper analyzes some aspects of the computational power of neural networks using
integer weights in a very restricted range. Using limited range integer values opens the road …

In an example, a circuit of a neural network implemented in an integrated circuit (IC)
includes a layer of hardware neurons, the layer including a plurality of inputs, a plurality of …

A synthesis system based on a circuit simulator and a silicon assembler for analog neural
networks to be implemented in MOS technology is presented. The system approximates on …

(57) ABSTRACT A neural network system includes an input layer, one or more hidden
layers, and an output layer. The input layer receives a training set including a sequence of …

The paper overviews recent developments concerning optimal (from the point of view of size
and depth) implementations of comparison using threshold gates. We detail a class of …

Estimating a priori the size of neural networks for achieving high classification accuracy is a
hard problem. Existing studies provide theoretical upper bounds on the size of neural …

This paper relies on the entropy of a data-set (ie, number-of-bits) to prove tight bounds on
the size of neural networks solving a classification problem. First, based on a sequence of …