… The MLP had j x k inputs and a single output node, and was trained to output a high value
(1.0) when … system, using the VLSI chip described by Myers, Vincent and Orrey in Chapter 16. …

A CMOS integrated circuit is described which is capable of implementing very large digital
neural networks of the multilayer perceptron (MLP) form. It incorporates on-chip training using …

The development of an integrated circuit known as HANNIBAL (Hardware Architecture for
Neural Networks Implementing Backpropagation Algorithm Learning) is described in this paper…

This paper describes an automatic method for locating facial features using arrays of neural
networks. The method uses multilayer perceptions (MLPs) for localised feature extraction …

… During weight updating a flag is set if potential overflow is detected in any of the j-th neuron’s
weights and if n ( jh . If the flag is set then the j-th neurons’s weights arc halved and nu) is …

This paper considers the digital VLSI implementation of neural nets, with particular emphasis
on a particular NN; the Multi-layer Perceptron (MLP) trained using the Back Propagation (…

Bipolar disorder (BP) is a disabling and often life-threatening disorder that affects ≈1% of
the population worldwide. To identify genetic variants that increase the risk of BP, we …

Borderline personality disorder (BOR) is determined by environmental and genetic factors,
and characterized by affective instability and impulsivity, diagnostic symptoms also observed …

A two-stage neural vision system for locating facial features is described. The first stage
generates search regions in an image at low spatial resolution, and the second pinpoints the …

In this chapter the development of a CMOS integrated circuit known as HANNIBAL (hardware
architecture for neural networks implementing backpropagation algorithm learning) [1] is …