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Principles of Artificial Neural Networks by Daniel Graupe

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Principles of Artificial Neural Networks by Daniel Graupe is digital courses, ebook, digital audio and DVD… not physical product. We will sent a download link lifetime to your email order. Or you can update your courses at “My Downloads“

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Principles of Artificial Neural Networks by Daniel Graupe

Principles of Artificial Neural Networks by Daniel Graupe

Principles of Artificial Neural Networks by Daniel Graupe

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Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond.This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained.The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.Contents: Introduction and Role of Artificial Neural NetworksFundamentals of Biological Neural NetworksBasic Principles of ANNs and Their Early StructuresThe PerceptronThe MadalineBack PropagationHopfield NetworksCounter PropagationLarge Scale Memory Storage and Retrieval (LAMSTAR) NetworkAdaptive Resonance TheoryThe Cognitron and the NeocognitronStatistical TrainingRecurrent (Time Cycling) Back Propagation Networks
Readership: Graduate and advanced senior students in artificial intelligence, pattern recognition & image analysis, neural networks, computational economics and finance, and biomedical engineering.

What is Self – Help

Self-help or self-improvement is a self-guided improvement—economically, intellectually, or emotionally—often with a substantial psychological basis.
Many different self-help group programs exist, each with its own focus, techniques, associated beliefs, proponents and in some cases, leaders.
Concepts and terms originating in self-help culture and Twelve-Step culture, such as recovery, dysfunctional families, and codependency have become firmly integrated in mainstream language.

Self-help often utilizes publicly available information or support groups, on the Internet as well as in person, where people in similar situations join together.
From early examples in self-driven legal practice and home-spun advice, the connotations of the word have spread and often apply particularly to education, business,
psychology and psychotherapy, commonly distributed through the popular genre of self-help books.
According to the APA Dictionary of Psychology, potential benefits of self-help groups that professionals may not be able to provide include friendship,
emotional support, experiential knowledge, identity, meaningful roles, and a sense of belonging.

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