Neural Networks In C
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Practical Neural Network Recipes In C
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Author : Timothy Masters
language : en
Publisher: Morgan Kaufmann
Release Date : 1993
Practical Neural Network Recipes In C written by Timothy Masters and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with C (Computer program language) categories.
This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to produce a working program implementing that network. The book provides guidance along the entire problem-solving path, including designing the training set, preprocessing variables, training and validating the network, and evaluating its performance. Though the book is not intended as a general course in neural networks, no background in neural works is assumed and all models are presented from the ground up. The principle focus of the book is the three layer feedforward network, for more than a decade as the workhorse of professional arsenals. Other network models with strong performance records are also included. Bound in the book is an IBM diskette that includes the source code for all programs in the book. Much of this code can be easily adapted to C compilers. In addition, the operation of all programs is thoroughly discussed both in the text and in the comments within the code to facilitate translation to other languages.
Pattern Recognition With Neural Networks In C
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Author : Abhijit S. Pandya
language : en
Publisher: CRC Press
Release Date : 2020-10-12
Pattern Recognition With Neural Networks In C written by Abhijit S. Pandya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-12 with Computers categories.
The addition of artificial neural network computing to traditional pattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical guide to the application of artificial neural networks. Geared toward the practitioner, Pattern Recognition with Neural Networks in C++ covers pattern classification and neural network approaches within the same framework. Through the book's presentation of underlying theory and numerous practical examples, readers gain an understanding that will allow them to make judicious design choices rendering neural application predictable and effective. The book provides an intuitive explanation of each method for each network paradigm. This discussion is supported by a rigorous mathematical approach where necessary. C++ has emerged as a rich and descriptive means by which concepts, models, or algorithms can be precisely described. For many of the neural network models discussed, C++ programs are presented for the actual implementation. Pictorial diagrams and in-depth discussions explain each topic. Necessary derivative steps for the mathematical models are included so that readers can incorporate new ideas into their programs as the field advances with new developments. For each approach, the authors clearly state the known theoretical results, the known tendencies of the approach, and their recommendations for getting the best results from the method. The material covered in the book is accessible to working engineers with little or no explicit background in neural networks. However, the material is presented in sufficient depth so that those with prior knowledge will find this book beneficial. Pattern Recognition with Neural Networks in C++ is also suitable for courses in neural networks at an advanced undergraduate or graduate level. This book is valuable for academic as well as practical research.
Object Oriented Neural Networks In C
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Author : Joey Rogers
language : en
Publisher: Morgan Kaufmann
Release Date : 1997
Object Oriented Neural Networks In C written by Joey Rogers and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.
"This book is distinctive in that it implements nodes and links as base objects and then composes them into four different kinds of neural networks. Roger's writing is clear....The text and code are both quite readable. Overall, this book will be useful to anyone who wants to implement neural networks in C++ (and, to a lesser extent, in other object-oriented programming languages.)...I recommend this book to anyone who wants to implement neural networks in C++."--D.L. Chester, Newark, Delaware in COMPUTING REVIEWSObject-Oriented Neural Networks in C++ is a valuable tool for anyone who wants to understand, implement, or utilize neural networks. This book/disk package provides the reader with a foundation from which any neural network architecture can beconstructed. The author has employed object-oriented design and object-oriented programming concepts to develop a set of foundation neural network classes, and shows how these classes can be used to implement a variety of neural network architectures with a great deal of ease and flexibility. A wealth of neural network formulas (with standardized notation), object code implementations, and examples are provided to demonstrate the object-oriented approach to neural network architectures and to facilitatethe development of new neural network architectures. This is the first book to take full advantage of the reusable nature of neural network classes. Key Features * Describes how to use the classes provided to implement a variety of neural network architectures including ADALINE, Backpropagation, Self-Organizing, and BAM * Provides a set of reusable neural network classes, created in C++, capable of implementing any neural network architecture * Includes an IBM disk of the source code for the classes, which is platform independent * Includes an IBM disk with C++ programs described in the book
Neural Networks In C
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Author : Adam Blum
language : en
Publisher:
Release Date : 1992
Neural Networks In C written by Adam Blum and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with C++ (Bilgisayar program dili) categories.
Interest in this area is at an all-time high. Fully explains how to apply neural networks to real-world problems, focusing on the practical side of building neural network applications. Besides providing a wealth of examples in C++, full coverage of three major application areas of neural network programming is included along with a complete C++ class library especially designed for neural network usage.
Practical Neural Network Recipies In C
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Author : Masters
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Practical Neural Network Recipies In C written by Masters and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.
This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to produce a working program implementing that network. The book provides guidance along the entire problem-solving path, including designing the training set, preprocessing variables, training and validating the network, and evaluating its performance. Though the book is not intended as a general course in neural networks, no background in neural works is assumed and all models are presented from the ground up. The principle focus of the book is the three layer feedforward network, for more than a decade as the workhorse of professional arsenals. Other network models with strong performance records are also included. Bound in the book is an IBM diskette that includes the source code for all programs in the book. Much of this code can be easily adapted to C compilers. In addition, the operation of all programs is thoroughly discussed both in the text and in the comments within the code to facilitate translation to other languages.
Applying Neural Networks
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Author : Kevin Swingler
language : en
Publisher: Morgan Kaufmann
Release Date : 1996
Applying Neural Networks written by Kevin Swingler and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.
This book is designed to enable the reader to design and run a neural network-based project. It presents everything the reader will need to know to ensure the success of such a project. The book contains a free disk with C and C++ programs, which implement many of the techniques discussed in the book.
Neural Networks In C
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Author : Adam Blum
language : en
Publisher:
Release Date : 1992
Neural Networks In C written by Adam Blum and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with C++ (Computer program language) categories.
Pattern Recognition With Neural Networks In C
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Author : Abhijit S. Pandya
language : en
Publisher: CRC Press
Release Date : 2019-12-17
Pattern Recognition With Neural Networks In C written by Abhijit S. Pandya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-17 with categories.
The addition of artificial network computing to traditional pattern recognition has given rise to a new, different, and more powerful methodology that is presented in this practical guide to the application of artificial neural networks. The material covered in the book is accessible to working engineers with little or no explicit background in neural networks.
Hands On Neural Network Programming With C
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Author : Matt R. Cole
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-09-29
Hands On Neural Network Programming With C written by Matt R. Cole and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-29 with Computers categories.
Create and unleash the power of neural networks by implementing C# and .Net code Key FeaturesGet a strong foundation of neural networks with access to various machine learning and deep learning librariesReal-world case studies illustrating various neural network techniques and architectures used by practitionersCutting-edge coverage of Deep Networks, optimization algorithms, convolutional networks, autoencoders and many moreBook Description Neural networks have made a surprise comeback in the last few years and have brought tremendous innovation in the world of artificial intelligence. The goal of this book is to provide C# programmers with practical guidance in solving complex computational challenges using neural networks and C# libraries such as CNTK, and TensorFlowSharp. This book will take you on a step-by-step practical journey, covering everything from the mathematical and theoretical aspects of neural networks, to building your own deep neural networks into your applications with the C# and .NET frameworks. This book begins by giving you a quick refresher of neural networks. You will learn how to build a neural network from scratch using packages such as Encog, Aforge, and Accord. You will learn about various concepts and techniques, such as deep networks, perceptrons, optimization algorithms, convolutional networks, and autoencoders. You will learn ways to add intelligent features to your .NET apps, such as facial and motion detection, object detection and labeling, language understanding, knowledge, and intelligent search. Throughout this book, you will be working on interesting demonstrations that will make it easier to implement complex neural networks in your enterprise applications. What you will learnUnderstand perceptrons and how to implement them in C#Learn how to train and visualize a neural network using cognitive servicesPerform image recognition for detecting and labeling objects using C# and TensorFlowSharpDetect specific image characteristics such as a face using Accord.NetDemonstrate particle swarm optimization using a simple XOR problem and EncogTrain convolutional neural networks using ConvNetSharpFind optimal parameters for your neural network functions using numeric and heuristic optimization techniques.Who this book is for This book is for Machine Learning Engineers, Data Scientists, Deep Learning Aspirants and Data Analysts who are now looking to move into advanced machine learning and deep learning with C#. Prior knowledge of machine learning and working experience with C# programming is required to take most out of this book
Neural Network And Fuzzy Logic Applications In C C
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Author : Stephen T Welstead
language : en
Publisher:
Release Date : 1994-08-01
Neural Network And Fuzzy Logic Applications In C C written by Stephen T Welstead and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-08-01 with categories.