《Neural Networks for Pattern Recognition》是由Christopher M. Bishop编写的机器学习权威著作，系统阐述了神经网络在模式识别中的理论与实践。该书从神经网络基础架构入手，深入探讨了反向传播算法、过拟合防治策略等技术细节，并辅以手写数字识别等经典案例。其在支持向量机、医学图像处理等跨领域研究中被广泛引用，确立...
Engineers in pattern recognition often classify the process of self-organization into supervised learning (or learning-with-a-teacher) and unsupervised learning (or learning-without-a-teacher). A famous example of a classical network that can be trained by supervised learning is the three-layered ...
nprtoolopens theNeural Net Pattern Recognitionapp. For more information and an example of its usage, seePattern Recognition with a Shallow Neural Network. Tip To interactively build and visualize deep learning neural networks, use theDeep Network Designerapp. For more information, seeGet Started with...
Edited by: Omid Omidvar and Judith Dayhoff About the book Browse this book By table of contents Book description This book is one of the most up-to-date and cutting-edge texts available on the rapidly growing application area of neural networks. Neural Networks and Pattern Recognition focuses....
These two recent books are important additions to the rapidly growing body of literature on pattern recognition and artificial neural networks. According to current definition and usage, pattern recognition "refers to a technology that recognizes and analyzes patterns automatically by machine" (Boden ...
这一篇是整个第五章的精华了,会重点介绍一下Neural Networks的训练方法——反向传播算法(backpropagation,BP),这个算法提出到现在近30年时间都没什么变化,可谓极其经典。也是deep learning的基石之一。还是老样子,下文基本是阅读笔记(句子翻译+自己理解),把书里的内容梳理一遍,也不为什么目的,记下来以后自己可以翻阅用。
In recent years neural computing has emerged as a practical technology, with successful applications in many fields. The majority of these applications are concerned with problems in pattern recognition, and make use of feed-forward network architectures such as the multi-layer perceptron and the ...
This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, the book describes techniques for modelling probability density functions, and discusses the properties and...
在模式识别领域,该方法最为典型的算法是本章节将会讨论 的前向神经网络(feed-forward neural network,后面简称NN),或者称为多层感知器(multilayer perceptron)。(注:这里多层模型是连续的,如sigmoid函数,而perceptron方法原本是不连续的;perceptron方法在PRML书中没有介绍,后面根据其他的资料单独写一篇)。很多情况下,NN...
In a neural network assembly for use in pattern recognition, a memory region memorizes reference patterns along with their categories. A pattern associator neural network is connected to the memory re