9783030981396 - cybernetics 2.0: a general theory of adaptivity and homeostasis in the brain and in the body: 14 di widrow, bernard (14 risultati)
Lingua: Inglese
Editore: Springer, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Lingua: Inglese
Editore: Springer, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Condizione: New. 1st ed. 2023 edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: SPRINGER NP, 2023
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Condizione: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if t…he Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Lingua: Inglese
Editore: Springer Nature, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Hardcover. Condizione: Brand New. 1st edition. 307 pages. 9.75x6.50x1.00 inches. In Stock.
Lingua: Inglese
Editore: Springer International Publishing, Springer Nature Switzerland, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book takes the notions of adaptivity and learning from the realm of engineering into the realm of biology and natural processes. It introduces a Hebbian-LMS algorithm, an integration of unsupervised Hebbian learning and supervised LMS learning in ne…ural networks, as a mathematical representation of a general theory for synaptic learning in the brain, and adaptation and functional control of homeostasis in living systems. Written in a language that is able to address students and scientists with different backgrounds, this book accompanies readers on a unique journey through various homeostatic processes in living organisms, such as body temperature control and synaptic plasticity, explaining how the Hebbian-LMS algorithm can help understand them, and suggesting some open questions for future research. It also analyses cell signalling pathways from an unusual perspective, where hormones and hormone receptors are shown to be regulated via the principles of the Hebbian-LMS algorithm. It further discusses addiction and pain, and various kinds of mood disorders alike, showing how they can be modelled with the Hebbian-LMS algorithm. For the first time, the Hebbian-LMS algorithm, which has been derived from a combination of Hebbian theory from the neuroscience field and the LMS algorithm from the engineering field of adaptive signal processing, becomes a potent model for understanding how biological regulation works. Thus, this book is breaking new ground in neuroscience by providing scientists with a general theory for how nature does control synaptic learning. It then goes beyond that, showing that the same principles apply to hormone-mediated regulation of physiological processes. In turn, the book tackles in more depth the concept of learning. It covers computer simulations and strategies for training neural networks with the Hebbian-LMS algorithm, demonstrating that the resulting algorithms are able to identify relationships between unknown input patterns. It shows how this can translate in useful ideas to understand human memory and design cognitive structures. All in all, this book offers an absolutely, unique, inspiring reading for biologists, physiologists, and engineers, paving the way for future studies on what we could call the nature's secret learning algorithm.
Lingua: Inglese
Editore: Springer, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Condizione: New.
Lingua: Inglese
Editore: Springer, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Condizione: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Lingua: Inglese
Editore: Springer, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer International Publishing, Springer Nature Switzerland Okt 2022, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book takes the notions of adaptivity and learning from the realm of engineering into the realm of biology and natural processes. It introduces a Hebbian-LMS algorithm, an integration of unsupervised Hebbian learning and supervised LM…S learning in neural networks, as a mathematical representation of a general theory for synaptic learning in the brain, and adaptation and functional control of homeostasis in living systems. Written in a language that is able to address students and scientists with different backgrounds, this book accompanies readers on a unique journey through various homeostatic processes in living organisms, such as body temperature control and synaptic plasticity, explaining how the Hebbian-LMS algorithm can help understand them, and suggesting some open questions for future research. It also analyses cell signalling pathways from an unusual perspective, where hormones and hormone receptors are shown to be regulated via the principles of the Hebbian-LMS algorithm. It further discusses addiction and pain, and various kinds of mood disorders alike, showing how they can be modelled with the Hebbian-LMS algorithm. For the first time, the Hebbian-LMS algorithm, which has been derived from a combination of Hebbian theory from the neuroscience field and the LMS algorithm from the engineering field of adaptive signal processing, becomes a potent model for understanding how biological regulation works. Thus, this book is breaking new ground in neuroscience by providing scientists with a general theory for how nature does control synaptic learning. It then goes beyond that, showing that the same principles apply to hormone-mediated regulation of physiological processes. In turn, the book tackles in more depth the concept of learning. It covers computer simulations and strategies for training neural networks with the Hebbian-LMS algorithm, demonstrating that the resulting algorithms are able to identify relationships between unknown input patterns. It shows how this can translate in useful ideas to understand human memory and design cognitive structures. All in all, this book offers an absolutely, unique, inspiring reading for biologists, physiologists, and engineers, paving the way for future studies on what we could call the nature's secret learning algorithm. 344 pp. Englisch.
Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|Springer, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Da: moluna, Greven, Germaniamoluna
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book takes the notions of adaptivity and learning from the realm of engineering into the realm of biology and natural processes. It introduces a Hebbian-LMS algorithm, an integration of unsupervised He…bbian learning and supervised LMS learning in ne.
Lingua: Inglese
Editore: Springer, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, Springer Okt 2022, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book takes the notions of adaptivity and learning from the realm of engineering into the realm of biology and natural processes. It introduces a Hebbian-LMS algorithm, an integration of unsupervised Hebbian learning and supervised LMS le…arning in neural networks, as a mathematical representation of a general theory for synaptic learning in the brain, and adaptation and functional control of homeostasis in living systems. Written in a language that is able to address students and scientists with different backgrounds, this book accompanies readers on a unique journey through various homeostatic processes in living organisms, such as body temperature control and synaptic plasticity, explaining how the Hebbian-LMS algorithm can help understand them, and suggesting some open questions for future research. It also analyses cell signalling pathways from an unusual perspective, where hormones and hormone receptors are shown to be regulated via the principles of the Hebbian-LMS algorithm. It further discusses addiction and pain, and various kinds of mood disorders alike, showing how they can be modelled with the Hebbian-LMS algorithm. For the first time, the Hebbian-LMS algorithm, which has been derived from a combination of Hebbian theory from the neuroscience field and the LMS algorithm from the engineering field of adaptive signal processing, becomes a potent model for understanding how biological regulation works. Thus, this book is breaking new ground in neuroscience by providing scientists with a general theory for how nature does control synaptic learning. It then goes beyond that, showing that the same principles apply to hormone-mediated regulation of physiological processes. In turn, the book tackles in more depth the concept of learning. It covers computer simulations and strategies for training neural networks with the Hebbian-LMS algorithm, demonstrating that the resulting algorithms are able to identify relationships between unknown input patterns. It shows how this can translate in useful ideas to understand human memory and design cognitive structures. All in all, this book offers an absolutely, unique, inspiring reading for biologists, physiologists, and engineers, paving the way for future studies on what we could call the nature's secret learning algorithm.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 344 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2022
Serie: Springer Series on Bio- and Neurosystems, Libro 8 di 9. Libro 8 di 9 - Springer Series on Bio- and Neurosystems
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND.
