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#PBIB:2001.3 --- Neural networks (Computer science) --- Neural networks (Neurobiology) --- Neural networks (Computer science). --- Neural networks (Neurobiology). --- Biological neural networks --- Nets, Neural (Neurobiology) --- Networks, Neural (Neurobiology) --- Neural nets (Neurobiology) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Cognitive neuroscience --- Neurobiology --- Neural circuitry --- Artificial intelligence --- Natural computation --- Soft computing

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This book is a comprehensive reference in the field of neural networks and genome informatics. The tutorial of neural network foundations introduces basic neural network technology and terminology. This is followed by an in-depth discussion of special system designs for building neural networks for genome informatics, and broad reviews and evaluations of current state-of-the-art methods in the field. This book concludes with a description of open research problems and future research directions.

Genetics --- Neural networks (Computer science) --- Bioinformatics. --- Genomes. --- Data processing. --- Bio-informatics --- Biological informatics --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Genomics --- Haploidy --- Biology --- Information science --- Computational biology --- Systems biology --- Artificial intelligence --- Natural computation --- Soft computing --- Embryology --- Mendel's law --- Adaptation (Biology) --- Breeding --- Chromosomes --- Heredity --- Mutation (Biology) --- Variation (Biology) --- Data processing

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Neural networks and fuzzy techniques are among the most promising approaches to pattern recognition. Neuro-fuzzy systems aim at combining the advantages of the two paradigms. This book is a collection of papers describing state-of-the-art work in this emerging field. It covers topics such as feature selection, classification, classifier training, and clustering. Also included are applications of neuro-fuzzy systems in speech recognition, land mine detection, medical image analysis, and autonomous vehicle control. The intended audience includes graduate students in computer science and related fields, as well as researchers at academic institutions and in industry.

Pattern recognition systems. --- Fuzzy systems. --- Neural networks (Computer science) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Systems, Fuzzy --- System analysis --- Fuzzy logic --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Fuzzy systems --- Pattern recognition systems --- 681.3*I51 --- 681.3*I51 Models: deterministic; fuzzy set; geometric; statistical; structural (Patternrecognition) --- Models: deterministic; fuzzy set; geometric; statistical; structural (Patternrecognition)

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Neural networks (Computer science) --- Self-organizing systems --- Topographic maps --- Brain Mapping --- Neural Networks (Computer) --- #TELE:SISTA --- 681.3*I26 --- Hypsographic maps --- Hypsometric maps --- Maps, Topographic --- Relief maps --- Topo maps --- Topographical maps --- Maps --- Learning systems (Automatic control) --- Self-optimizing systems --- Cybernetics --- Intellect --- Learning ability --- Synergetics --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Computational Neural Networks --- Connectionist Models --- Models, Neural Network --- Neural Network Models --- Perceptrons --- Computational Neural Network --- Computer Neural Network --- Computer Neural Networks --- Connectionist Model --- Model, Connectionist --- Model, Neural Network --- Models, Connectionist --- Network Model, Neural --- Network Models, Neural --- Network, Computational Neural --- Network, Computer Neural --- Network, Neural (Computer) --- Networks, Computational Neural --- Networks, Computer Neural --- Networks, Neural (Computer) --- Neural Network (Computer) --- Neural Network Model --- Neural Network, Computational --- Neural Network, Computer --- Neural Networks, Computational --- Perceptron --- 681.3*I26 Learning: analogies; concept learning; induction; knowledge acquisition; language acquisition; parameter learning (Artificial intelligence)--See also {681.3*K32} --- Learning: analogies; concept learning; induction; knowledge acquisition; language acquisition; parameter learning (Artificial intelligence)--See also {681.3*K32} --- methods --- Artificial intelligence. Robotics. Simulation. Graphics --- Neural networks (Computer science). --- Self-organizing systems. --- Topographic maps.

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Multi-Valued and Universal Binary Neurons deals with two new types of neurons: multi-valued neurons and universal binary neurons. These neurons are based on complex number arithmetic and are hence much more powerful than the typical neurons used in artificial neural networks. Therefore, networks with such neurons exhibit a broad functionality. They can not only realise threshold input/output maps but can also implement any arbitrary Boolean function. Two learning methods are presented whereby these networks can be trained easily. The broad applicability of these networks is proven by several case studies in different fields of application: image processing, edge detection, image enhancement, super resolution, pattern recognition, face recognition, and prediction. The book is hence partitioned into three almost equally sized parts: a mathematical study of the unique features of these new neurons, learning of networks of such neurons, and application of such neural networks. Most of this work was developed by the first two authors over a period of more than 10 years and was only available in the Russian literature. With this book we present the first comprehensive treatment of this important class of neural networks in the open Western literature. Multi-Valued and Universal Binary Neurons is intended for anyone with a scholarly interest in neural network theory, applications and learning. It will also be of interest to researchers and practitioners in the fields of image processing, pattern recognition, control and robotics.

Artificial intelligence. --- Computer engineering. --- Physics. --- Neural networks (Computer science) --- Computer Science --- Engineering & Applied Sciences --- Physics --- Physical Sciences & Mathematics --- Atomic Physics --- Neurale netwerken (Informatica) --- Réseaux neuraux (Informatique) --- Neural networks (Computer scinece) --- Academic collection --- #TELE:ELEN --- 681.3*I5 --- 681.3*I5 Pattern recognition (Computing methodologies) --- Pattern recognition (Computing methodologies) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Statistical physics. --- Complex Systems. --- Artificial Intelligence. --- Control, Robotics, Mechatronics. --- Electrical Engineering. --- Signal, Image and Speech Processing. --- Statistical Physics and Dynamical Systems. --- Mathematical statistics --- Computers --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Statistical methods --- Design and construction --- Dynamical systems. --- Control engineering. --- Robotics. --- Mechatronics. --- Electrical engineering. --- Signal processing. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Electric engineering --- Engineering --- Mechanical engineering --- Microelectronics --- Microelectromechanical systems --- Automation --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Programmable controllers --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Statics