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Title Artificial intelligence in the age of neural networks and brain computing / edited by Robert Kozma, Cesare Alippi, Yoonsuck Choe, Francesco Carlo Morabito.

Publication Info. London, United Kingdom : Academic Press, an imprint of Elsevier, [2019]


Location Call No. OPAC Message Status
 Axe Elsevier ScienceDirect Ebook  Electronic Book    ---  Available
 Axe Elsevier ScienceDirect Ebook    ---  Available
Description 1 online resource (xiii, 324 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
data file
Occupation/field of activity group: occ Engineers lcdgt
Occupation/field of activity group: occ University and college faculty members lcdgt
Gender group: gdr Men lcdgt
Bibliography Includes bibliographical references and index.
Note Online resource; title from PDF title page (ScienceDirect, viewed November 5, 2018).
Summary With contributions from pioneers and experts in the field of neural networks, this book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. -- Edited summary from book.
Contents Chapter 1 Nature's learning rule: The Hebbian-LMS algorithm / Bernard Widrow, Youngsik Kim, Dookun Park and Jose Krause Perin -- Introduction -- ADALINE and the LMS algorithm, From the 1950s -- Unsupervised learning with Adaline, From the 1960s -- Robert Lucky's adaptive equalization, From the 1960s -- Bootstrap learning with a Sigmoidal neuron -- Bookstrap learning with a more "Biologically correct" Sigmoidal neuron -- Other clustering algorithms -- A general Hebbian-LMS algorithm -- The synapse -- Postulates of synaptic plasticity -- The postulates and the Hebbian-LMS algorithm -- Nature's Hebbian-LMS algorithm -- Conclusion -- Chapter 2 A half century of progress toward a unified neural theory of mind and brain with applications to autonomous adaptive agents and mental disorders / Stephen Grossberg -- Towards a unified theory of mind and brain -- A theoretical method for linking brain to mind: The method of minimal anatomies -- Revolutionary brain paradigms: Complementary computing and laminar computing -- The what and where cortical streams are complementary -- Adaptive resonance theory -- Vector associative maps for spatial representation and action -- Homologous laminar cortical circuits for all biological intelligence: Beyond Bayes -- Why a unified theory is possible: Equations, modules, and architectures -- All conscious states are resonant states -- The varieties of brain resonances and the conscious experiences that they support -- Why does resonance trigger consciousness? -- Towards autonomous adaptive intelligent agents and clinical therapies in society -- References -- Chapter 3 Third Gen AI as human experience based expert systems / Harold Szu and the AI working group -- Introduction -- Third gen AI -- MFE gradient descent -- Conclusion -- 4 The brain-mind-computer trichotomy: Hermeneutic approach / Péter Érdi -- Dichotomies -- Hermeneutics -- Schizophrenia: A broken hermeneutic cycle -- Toward the algorithms of neural/mental hermeneutic interpretation -- Chapter 5 From synapses to ephapsis: Embodied cognition and wearable personal assistants / Roman Ormandy -- Neural networks and neural fields -- Ephapsis -- Embodied cognition -- Wearable personal assistants -- References -- Chapter 6 Evolving and spiking connectionist systems for brain-inspired artificial intelligence / Nikola Kasabov -- From Aristotle's logic to artificial neural networks and hybrid systems -- Evolving connectionist systems (ECOS) -- Spiking neural networks (SNN) as brain-inspired ANN -- Brain-like AI systems based on SNN, NeuCube, deep learning algorithms -- Conclusion -- Chapter 7 Pitfalls and opportunities in the development and evaluation of artificial intelligence systems / David G. Brown and Frank W. Samuelson -- Introduction -- AI development -- AI evaluation -- Variability and bias in our performance estimates -- Conclusion -- Chapter 8 The new AI: Basic concepts, urgent risks and opportunities in the Internet of Things / Paulo J. Werbos -- Introduction and overview -- Brief history and foundations of the deep learning revolution -- From RNNs to mouse-level computational intelligence: Next big things and beyond -- Need for new directions in understanding brain and mind -- Information technology (IT) for human survival: An urgent unmet challenge -- References -- Chapter 9 Theory of the brain and mind: Visions and history / Daniel S. Levine -- Early history -- Emergence of some neural network principles -- Neural networks enter mainstream science -- Is computational neuroscience separate from neural network theory? -- Discussion -- References -- Chapter 10 Computers versus brains: Game is over or more to come? / Robert Kozma -- Introduction -- AI approaches -- Metastability in cognition and in brain dynamics -- Pragmatic implementation of complementarity for new AI -- Acknowledgments -- References -- Chapter 11 Deep learning apporaches to electrophysiological multivariate time-series analysis / Francesco Carlo Morabito, Maurizio Campolo, Cosimo leracitano and Nadia Mammone -- Introduction -- The neural network approach -- Deep architectures and learning -- Electrophysiological time-series -- Deep learning models for EEG signal processing -- Future directions of research -- Conclusion -- Further reading -- Chapter 12 Computational intelligence in the time of cyber-physical systems and the Internet of Things / Cesare Alippi and Seiichi Ozawa -- Introduction -- System architecture -- Energy harvesting and management -- Learning in nonstationary environments -- Model-free fault diagnosis systems -- Cybersecurity -- Conclusions -- Acknowledgments -- References -- Chapter 13 Multiview learning in biomedical applications / Angela Serra, Paola Galdi and Roberto Tagliaferri -- Introduction -- Multiview learning -- Multiview learning in bioinformatics -- Multiview learning in neuroinformatics -- Deep multimodal feature learning -- Conclusions -- References -- Chapter 14 Meaning versus information, prediction versus memory, and question versus answer / Yoonsuck Choe -- Introduction -- Meaning versus information -- Prediction versus memory -- Question versus answer -- Discussion -- Conclusion -- Acknowledgments -- References -- Chapter 15 Evolving deep neural networks / Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Daniel Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy and Babak Hodjat -- Introduction -- Background and related work -- Evolution of deep learning architectures -- Evolution of LSTM architectures -- Evolution of LSTM architectures -- Application case study: Image captioning for the blind -- Discussion and future work -- Conclusion -- References.
Subject Artificial intelligence.
Neural networks (Computer science)
Brain-computer interfaces.
Artificial Intelligence
Neural Networks, Computer
Intelligence artificielle.
Réseaux neuronaux (Informatique)
Interfaces cerveau-ordinateur.
artificial intelligence.
COMPUTERS -- General.
Artificial intelligence. (OCoLC)fst00817247
Brain-computer interfaces. (OCoLC)fst01742078
Neural networks (Computer science) (OCoLC)fst01036260
Genre/Form Electronic books.
Added Author Kozma, Robert, editor.
Alippi, Cesare, editor.
Choe, Yoonsuck, editor.
Morabito, F. C. (Francesco Carlo), editor.
Other Form: Print version: Artificial intelligence in the age of neural networks and brain computing. London, United Kingdom : Academic Press, an imprint of Elsevier, [2019] 0128154802 9780128154809 (OCoLC)1013727193
ISBN 9780128162507 (electronic bk.)
0128162503 (electronic bk.)
9780128154809 (print)
0128154802 (print)
Standard No. AU@ 000064448503
AU@ 000064848627
AU@ 000065141262
AU@ 000068582531
CHBIS 011318714
CHVBK 55150417X
UKMGB 019118948

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