Artificial Neural Networks (2016) download ebook TXT, PDF, FB2
9781681175294 English 1681175290 "An artificial neuron network (ANN) is a computational model based on the structure and functions of biological neural networks. Information that flows through the network affects the structure of the ANN because a neural network changes - or learns, in a sense - based on that input and output. Artificial neural networks are relatively crude electronic models based on the neural structure of the brain. The brain basically learns from experience. It is natural proof that some problems that are beyond the scope of current computers are indeed solvable by small energy efficient packages. This brain modeling also promises a less technical way to develop machine solutions. This new approach to computing also provides a more graceful degradation during system overload than its more traditional counterparts. These biologically inspired methods of computing are thought to be the next major advancement in the computing industry. Even simple animal brains are capable of functions that are currently impossible for computers. Computers do rote things well, like keeping ledgers or performing complex math. But computers have trouble recognizing even simple patterns much less generalizing those patterns of the past into actions of the future. Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications. Artificial Neural Networks provide recent advances of architectures, methodologies, and applications of artificial neural networks. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks. This book will be of valuable for college and graduate students, and engineers in companies.
9781681175294 English 1681175290 "An artificial neuron network (ANN) is a computational model based on the structure and functions of biological neural networks. Information that flows through the network affects the structure of the ANN because a neural network changes - or learns, in a sense - based on that input and output. Artificial neural networks are relatively crude electronic models based on the neural structure of the brain. The brain basically learns from experience. It is natural proof that some problems that are beyond the scope of current computers are indeed solvable by small energy efficient packages. This brain modeling also promises a less technical way to develop machine solutions. This new approach to computing also provides a more graceful degradation during system overload than its more traditional counterparts. These biologically inspired methods of computing are thought to be the next major advancement in the computing industry. Even simple animal brains are capable of functions that are currently impossible for computers. Computers do rote things well, like keeping ledgers or performing complex math. But computers have trouble recognizing even simple patterns much less generalizing those patterns of the past into actions of the future. Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications. Artificial Neural Networks provide recent advances of architectures, methodologies, and applications of artificial neural networks. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks. This book will be of valuable for college and graduate students, and engineers in companies.