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Titlebook: Neuromorphic Cognitive Systems; A Learning and Memor Qiang Yu,Huajin Tang,Kay‘Tan Chen Book 2017 Springer International Publishing AG 2017

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發(fā)表于 2025-3-21 18:45:45 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Neuromorphic Cognitive Systems
副標題A Learning and Memor
編輯Qiang Yu,Huajin Tang,Kay‘Tan Chen
視頻videohttp://file.papertrans.cn/665/664235/664235.mp4
概述Discusses the computational principles underlying spike-based information processing and cognitive computation with a specific focus on learning and memory.Describes theoretical modeling and analysis
叢書名稱Intelligent Systems Reference Library
圖書封面Titlebook: Neuromorphic Cognitive Systems; A Learning and Memor Qiang Yu,Huajin Tang,Kay‘Tan Chen Book 2017 Springer International Publishing AG 2017
描述This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. .The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed...The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation pla
出版日期Book 2017
關鍵詞Cognitive Memory; Intelligent Systems; Neural Coding; Neuromorphic Cognitive Systems; Neuromorphic Compu
版次1
doihttps://doi.org/10.1007/978-3-319-55310-8
isbn_softcover978-3-319-85625-4
isbn_ebook978-3-319-55310-8Series ISSN 1868-4394 Series E-ISSN 1868-4408
issn_series 1868-4394
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 23:34:25 | 只看該作者
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Intelligent Systems Reference Libraryhttp://image.papertrans.cn/n/image/664235.jpg
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發(fā)表于 2025-3-22 11:55:46 | 只看該作者
Qiang Yu,Huajin Tang,Kay‘Tan ChenDiscusses the computational principles underlying spike-based information processing and cognitive computation with a specific focus on learning and memory.Describes theoretical modeling and analysis
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發(fā)表于 2025-3-22 12:57:48 | 只看該作者
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Rapid Feedforward Computation by Temporal Encoding and Learning with Spiking Neurons,g layer, followed by the final decision presented through the readout layer. The performance of the model is also analyzed and discussed. This chapter presents a general structure of SNN for pattern recognition, showing that the SNN has the ability to learn the real-world stimuli.
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發(fā)表于 2025-3-23 08:18:27 | 只看該作者
Precise-Spike-Driven Synaptic Plasticity for Hetero Association of Spatiotemporal Spike Patterns,plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters.
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