Издательство CRC Press, 2000, -358 pp.Neural networks are a new generation of information processing paradigms designed to mimic some of the behaviors of the human brain. These networks have gained tremendous popularity due to their ability to learn, recall and generalize from training data. A number of neural network paradigms have been reported in the last four decades, and in the last decade the neural networks have been refined and widely used by researchers and application engineers.
The main purpose of this book is to report recent advances in neural network paradigms and their applications. It is impossible to include all recent advances in this book; hence, only a sample has been included.A neuro-symbolic hybrid intelligent architecture with applications
New radial basis neural networks and their application in a large-scale handwritten digit recognition problem
Efficient neural network-based methodology for the design of multiple classifiers
Learning fine motion in robotics: design and experiments
A new neural network for adaptive pattern recognition of multichannel input signals
Lateral priming adaptive resonance theory (LAPART)-2: innovation in ART
Neural network learning in a travel reservation domain
Recent advances in neural network applications in process control
Monitoring internal combustion engines by neural network based virtual sensing

Neural architectures of fuzzy Petri nets

Издательство CRC Press, 2000, -358 pp.神经网络是新一代的信息处理范式，旨在模仿人脑的一些行为。由于这些网络具有从训练数据中学习、回忆和归纳的能力，因此获得了极大的欢迎。在过去的四十年中，已经报道了一些神经网络范式，在过去的十年中，神经网络得到了完善，并被研究人员和应用工程师广泛使用。

本书的主要目的是报告神经网络范式的最新进展及其应用。本书不可能包括所有的最新进展，因此，只收录了一个样本。神经符号混合智能架构与应用

新的径向基神经网络及其在大规模手写数字识别问题中的应用

基于神经网络的高效多分类器设计方法

机器人的精细运动学习：设计与实验

用于多通道输入信号的自适应模式识别的新型神经网络

侧向引力适应性共振理论（LAPART）-2：ART的创新

旅游预订领域的神经网络学习

神经网络在过程控制中应用的最新进展

通过基于神经网络的虚拟传感监测内燃机

模糊Petri网的神经结构