Artificial Neural Networks: Learning Algorithms, Performance Evaluation, and Applications
1.1 Overview We are living in a decade recently declared as the "Decade of the Brain". Neuroscientists may soon manage to work out a functional map of the brain, thanks to technologies that open windows on the mind. With the average human brain consisting of 15 billion neurons, roughly equ...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
1993
|
| Schriftenreihe: | The Springer International Series in Engineering and Computer Science
209 |
| Schlagworte: | |
| Online-Zugang: | BTU01 Volltext |
| Zusammenfassung: | 1.1 Overview We are living in a decade recently declared as the "Decade of the Brain". Neuroscientists may soon manage to work out a functional map of the brain, thanks to technologies that open windows on the mind. With the average human brain consisting of 15 billion neurons, roughly equal to the number of stars in our milky way, each receiving signals through as many as 10,000 synapses, it is quite a view. "The brain is the last and greatest biological frontier", says James Weston codiscoverer of DNA, considered to be the most complex piece of biological machinery on earth. After many years of research by neuroanatomists and neurophys iologists, the overall organization of the brain is well understood, but many of its detailed neural mechanisms remain to be decoded. In order to understand the functioning of the brain, neurobiologists have taken a bottom-up approach of studying the stimulus-response characteristics of single neurons and networks of neurons, while psy chologists have taken a top-down approach of studying brain func tions from the cognitive and behavioral level. While these two ap proaches are gradually converging, it is generally accepted that it may take another fifty years before we achieve a solid microscopic, intermediate, and macroscopic understanding of brain |
| Beschreibung: | 1 Online-Ressource (XV, 440 p) |
| ISBN: | 9781475745474 |
| DOI: | 10.1007/978-1-4757-4547-4 |
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| discipline | Informatik |
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| isbn | 9781475745474 |
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| spelling | Karayiannis, N. B. Verfasser aut Artificial Neural Networks Learning Algorithms, Performance Evaluation, and Applications by N. B. Karayiannis, A. N. Venetsanopoulos Boston, MA Springer US 1993 1 Online-Ressource (XV, 440 p) txt rdacontent c rdamedia cr rdacarrier The Springer International Series in Engineering and Computer Science 209 1.1 Overview We are living in a decade recently declared as the "Decade of the Brain". Neuroscientists may soon manage to work out a functional map of the brain, thanks to technologies that open windows on the mind. With the average human brain consisting of 15 billion neurons, roughly equal to the number of stars in our milky way, each receiving signals through as many as 10,000 synapses, it is quite a view. "The brain is the last and greatest biological frontier", says James Weston codiscoverer of DNA, considered to be the most complex piece of biological machinery on earth. After many years of research by neuroanatomists and neurophys iologists, the overall organization of the brain is well understood, but many of its detailed neural mechanisms remain to be decoded. In order to understand the functioning of the brain, neurobiologists have taken a bottom-up approach of studying the stimulus-response characteristics of single neurons and networks of neurons, while psy chologists have taken a top-down approach of studying brain func tions from the cognitive and behavioral level. While these two ap proaches are gradually converging, it is generally accepted that it may take another fifty years before we achieve a solid microscopic, intermediate, and macroscopic understanding of brain Computer Science Artificial Intelligence (incl. Robotics) Computer Systems Organization and Communication Networks Appl.Mathematics/Computational Methods of Engineering Circuits and Systems Statistical Physics, Dynamical Systems and Complexity Signal, Image and Speech Processing Computer science Computer organization Artificial intelligence Statistical physics Dynamical systems Applied mathematics Engineering mathematics Electronic circuits Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 s 1\p DE-604 Venetsanopoulos, A. N. aut Erscheint auch als Druck-Ausgabe 9781441951328 https://doi.org/10.1007/978-1-4757-4547-4 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Karayiannis, N. B. Venetsanopoulos, A. N. Artificial Neural Networks Learning Algorithms, Performance Evaluation, and Applications Computer Science Artificial Intelligence (incl. Robotics) Computer Systems Organization and Communication Networks Appl.Mathematics/Computational Methods of Engineering Circuits and Systems Statistical Physics, Dynamical Systems and Complexity Signal, Image and Speech Processing Computer science Computer organization Artificial intelligence Statistical physics Dynamical systems Applied mathematics Engineering mathematics Electronic circuits Neuronales Netz (DE-588)4226127-2 gnd |
| subject_GND | (DE-588)4226127-2 |
| title | Artificial Neural Networks Learning Algorithms, Performance Evaluation, and Applications |
| title_auth | Artificial Neural Networks Learning Algorithms, Performance Evaluation, and Applications |
| title_exact_search | Artificial Neural Networks Learning Algorithms, Performance Evaluation, and Applications |
| title_full | Artificial Neural Networks Learning Algorithms, Performance Evaluation, and Applications by N. B. Karayiannis, A. N. Venetsanopoulos |
| title_fullStr | Artificial Neural Networks Learning Algorithms, Performance Evaluation, and Applications by N. B. Karayiannis, A. N. Venetsanopoulos |
| title_full_unstemmed | Artificial Neural Networks Learning Algorithms, Performance Evaluation, and Applications by N. B. Karayiannis, A. N. Venetsanopoulos |
| title_short | Artificial Neural Networks |
| title_sort | artificial neural networks learning algorithms performance evaluation and applications |
| title_sub | Learning Algorithms, Performance Evaluation, and Applications |
| topic | Computer Science Artificial Intelligence (incl. Robotics) Computer Systems Organization and Communication Networks Appl.Mathematics/Computational Methods of Engineering Circuits and Systems Statistical Physics, Dynamical Systems and Complexity Signal, Image and Speech Processing Computer science Computer organization Artificial intelligence Statistical physics Dynamical systems Applied mathematics Engineering mathematics Electronic circuits Neuronales Netz (DE-588)4226127-2 gnd |
| topic_facet | Computer Science Artificial Intelligence (incl. Robotics) Computer Systems Organization and Communication Networks Appl.Mathematics/Computational Methods of Engineering Circuits and Systems Statistical Physics, Dynamical Systems and Complexity Signal, Image and Speech Processing Computer science Computer organization Artificial intelligence Statistical physics Dynamical systems Applied mathematics Engineering mathematics Electronic circuits Neuronales Netz |
| url | https://doi.org/10.1007/978-1-4757-4547-4 |
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