Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence
暫譯: 時間-空間、脈衝神經網絡與類腦人工智慧

Kasabov, Nikola K.

  • 出版商: Springer
  • 出版日期: 2019-01-19
  • 售價: $13,130
  • 貴賓價: 9.5$12,474
  • 語言: 英文
  • 頁數: 738
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 366258607X
  • ISBN-13: 9783662586075
  • 相關分類: 人工智慧
  • 海外代購書籍(需單獨結帳)

商品描述

Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author's contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.


商品描述(中文翻譯)

尖峰神經網絡(SNN)是受生物啟發的計算模型,內部以尖峰序列的方式表示和處理信息。本專著介紹了SNN的經典理論和應用,包括作者在該領域的原創貢獻。本書首次介紹了人腦中的深度學習和深度知識表示,以及受腦啟發的SNN,並進一步發展出新型的人工智慧系統,稱為受腦啟發的人工智慧(BI-AI)。BI-AI系統的應用範圍包括:認知腦數據(包括腦電圖 EEG、功能性磁共振成像 fMRI 和擴散張量成像 DTI);音視覺數據;腦機介面;生物神經信息學中的個性化建模;金融、環境和生態中的多感官流數據建模;數據壓縮;神經形態硬體實現。未來的方向,如多模態的整合,包括量子、分子和腦信息處理,將在最後一章中介紹。本書是一本針對研究生、研究人員和實務工作者的研究書籍,涵蓋計算機與信息科學、工程、應用數學、生物科學和神經科學等更廣泛的領域。

作者簡介

Nikola Kirilov Kasabov is Professor of neural networks and knowledge engineering and Director of the Knowledge Engineering and Discovery Research Institute (KEDRI) at the Auckland University of Technology (AUT), New Zealand. Born in Bulgaria, he has worked previously at the TU Sofia, University of Essex and University of Otago. He is fellow of IEEE, Fellow of the Royal Society (Academy) of New Zealand (RSNZ), Distinguished Fellow of the Royal Academy of Engineering UK and Visiting Professor at several universities, including: Shanghai Jia-Tong University; ETH and University of Zurich; RGU Scotland UK; University of Trento; University of Kaiserslautern; Universities of Twente and Maastricht. Prof Kasabov originated methods and systems for intelligent information processing, including: evolving connectionist systems, hybrid neuro-fuzzy systems, evolving- and brain -inspired spiking neural network architectures, quantum-inspired methods, methods for personalised modelling in bio and neuroinformatics, published in more than 600 works. He is Past President of the International Neural Network Society (INNS) and the current President of the Asia-Pacific Neural Network Society (APNNS). Prof Kasabov has received the INNS Ada Lovelace and Gabor Awards, APNNS Outstanding Achievements Award, RSNZ Medal, AUT Medal, Honourable Fellowship of the Bulgarian and the Greek Computer Societies, Pavlikeni Honourable Citizenship and other awards. He has been the editor of the Springer Handbook of Bio-/Neuro-informatics published by Springer in 2014 and of the related book series Springer Series on Bio- and Neurosystems.

作者簡介(中文翻譯)

尼古拉·基里洛夫·卡薩博夫(Nikola Kirilov Kasabov)是紐西蘭奧克蘭科技大學(Auckland University of Technology, AUT)神經網絡與知識工程的教授,以及知識工程與發現研究所(Knowledge Engineering and Discovery Research Institute, KEDRI)的主任。他出生於保加利亞,曾在索非亞科技大學(TU Sofia)、埃塞克斯大學(University of Essex)和奧塔哥大學(University of Otago)工作。他是IEEE的會士、新西蘭皇家學會(Royal Society of New Zealand, RSNZ)的會士、英國皇家工程院(Royal Academy of Engineering UK)的傑出會士,以及多所大學的訪問教授,包括:上海交通大學(Shanghai Jia-Tong University)、瑞士聯邦理工學院(ETH)和蘇黎世大學(University of Zurich)、蘇格蘭的羅伯特·戈登大學(RGU Scotland UK)、特倫托大學(University of Trento)、凱瑟斯勞滕大學(University of Kaiserslautern)、特溫特大學(University of Twente)和馬斯特里赫特大學(University of Maastricht)。卡薩博夫教授創造了智能信息處理的方法和系統,包括:演化連接主義系統、混合神經模糊系統、演化和腦啟發的脈衝神經網絡架構、量子啟發的方法、生物和神經信息學中的個性化建模方法,並發表了超過600篇作品。他曾擔任國際神經網絡學會(International Neural Network Society, INNS)的前任會長,並是亞太神經網絡學會(Asia-Pacific Neural Network Society, APNNS)的現任會長。卡薩博夫教授獲得了INNS的艾達·洛夫萊斯獎(Ada Lovelace Award)和加博爾獎(Gabor Award)、APNNS傑出成就獎、RSNZ獎章、AUT獎章、保加利亞和希臘計算機學會的榮譽會士、帕夫利基尼榮譽公民及其他獎項。他曾擔任2014年由Springer出版的《生物/神經信息學手冊》(Springer Handbook of Bio-/Neuro-informatics)的編輯,以及相關書系《Springer Series on Bio- and Neurosystems》的編輯。