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ICICA 2022
The 2022 2nd International Conference on Information, Control and Automation (ICICA 2022) was held on December 2nd-4th, 2022 in Chongqing, China (virtual event). Invited and contributed papers present the state-of-the-art research in information, control and automation. This workshop always welcomes a fruitful mix of experienced researchers and students, to allow a better understanding of related fields. The 2022 session of the information, control and automation was doubtlessly a great success. The program covered a wide variety of topics, namely Numerical Analysis, Information Theory, Genetic Algorithm, Distributed Control System, Industrial Control, Motors and Appliances, etc. The confere...
Synaptic Circuits and Functions in Bio-inspired Integrated Architectures
Based upon the most advanced human-made technology on this planet, CMOS integrated circuit technology, this dissertation examines the design of hardware components and systems to establish a technological foundation for the application of future breakthroughs in the intersection of AI and neuroscience. Humans have long imagined machines, robots, and computers that learn and display intelligence akin to animals and themselves. To advance the development of these machines, specialised research in custom-built hardware designed for specific types of computation, which mirrors the structure of powerful biological nervous systems, is especially important. This dissertation is driven by the quest ...
Understanding and Bridging the Gap between Neuromorphic Computing and Machine Learning, volume II
Towards the long-standing dream of artificial intelligence, two solution paths have been paved: (i) neuroscience-driven neuromorphic computing; (ii) computer science-driven machine learning. The former targets at harnessing neuroscience to obtain insights for brain-like processing, by studying the detailed implementation of neural dynamics, circuits, coding and learning. Although our understanding of how the brain works is still very limited, this bio-plausible way offers an appealing promise for future general intelligence. In contrast, the latter aims at solving practical tasks typically formulated as a cost function with high accuracy, by eschewing most neuroscience details in favor of br...
Spike-based learning application for neuromorphic engineering
Spiking Neural Networks (SNN) closely imitate biological networks. Information processing occurs in both spatial and temporal manner, making SNN extremely interesting for the pertinent mimicking of the biological brain. Biological brains code and transmit the sensory information in the form of spikes that capture the spatial and temporal information of the environment with amazing precision. This information is processed in an asynchronous way by the neural layer performing recognition of complex spatio-temporal patterns with sub-milliseconds delay and at with a power budget in the order of 20W. The efficient spike coding mechanism and the asynchronous and sparse processing and communication of spikes seems to be key in the energy efficiency and high-speed computation capabilities of biological brains. SNN low-power and event-based computation make them more attractive when compared to other artificial neural networks (ANN).
Neural Information Processing
The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.
Appropriation and Representation
Feng Menglong (1574–1646) was recognized as the most knowledgeable connoisseur of popular literature of his time. He is known today for compiling three famous collections of vernacular short stories, each containing forty stories, collectively known as Sanyan. Appropriation and Representation adapts concepts of ventriloquism and dialogism from Bakhtin and Holquist to explore Feng’s methods of selecting source materials. Shuhui Yang develops a model of development in which Feng’s approach to selecting and working with his source materials becomes clear. More broadly, Appropriation and Representation locates Feng Menglong’s Sanyan in the cultural milieu of the late Ming, including the archaist movement in literature, literati marginality and anxieties, the subversive use of folk works, and the meiren xiangcao tradition—appropriating a female identity to express male frustration. Against this background, a rationale emerges for Feng’s choice to elevate and promote the vernacular story while stepping back form an overt authorial role.
