… state of digital and optical hardware for neural networks, … One problem, which is shared by
much of the neural network … As a quick, self-guided tutorial exposition of neural networks and …

… architectures: Multi-layer perceptrons (MLP), radial basis function (RBF) networks and self-…
geometry for neural network learning. Other important neural network architectures will not be …

… digital VLSI implementations and discusses techniques for implementing high performance,
high capacity digital neural nets. … blocks useful in implementing digital networks. It then uses …

… neural network implementations is discussed. A flexible architecture that permits the realization
of arbitrary network … post facto construction of neural networks of arbitrary topology and …

… to non-linearity simplification in neural nets are presented. Both the solutions are based on
approximation of the sigmoidal mapper often used in neural networks (extensions are being …

… digital content such as images, audio, and videos. In this paper, we propose a digital
watermarking technology for neural networks… a watermark in deep neural network models to …

… digital soil maps. Thus, this study focuses on the development of a methodology based on
artificial neural net… In most cases, feed-forward artificial neural networks (ANN) with different …

… of digital systems to implement neural networks. We consider three options for implementing
neural networks in digital systems: serial computers, parallel systems with standard digital …

Problem statement: Handwriting number recognition is a challenging problem researchers
had been research into this area for so long especially in the recent years. In our study there …

… digital processors designed for neural networks. Obviously, the ANNs achieve their full
potential only when implemented on hardware structures characterized by parallel architecture [3]…