Cameron's Thesis


Book Description

Both the visualisation and management of large-scale computer hardware is difficult due to its distributed nature. This thesis develops a framework to support both these goals on the SpiNNaker neural network architecture - which can scale to more than a million processors. The solution provides visualisation and management to the SpiNNaker machine, traversing the hardware and software divide to provide a unified solution for the real-time monitoring of artificial neural networks, and the SpiNNaker hardware on which it runs. This book is the story of its development




Massively Parallel, Optical, and Neural Computing in the United States


Book Description

A survey of products and research projects in the field of highly parallel, optical and neural computers in the USA. It covers operating systems, language projects and market analysis, as well as optical computing devices and optical connections of electronic parts.




Algorithms and Architectures for Real-Time Control 1992


Book Description

This Workshop focuses on such issues as control algorithms which are suitable for real-time use, computer architectures which are suitable for real-time control algorithms, and applications for real-time control issues in the areas of parallel algorithms, multiprocessor systems, neural networks, fault-tolerance systems, real-time robot control identification, real-time filtering algorithms, control algorithms, fuzzy control, adaptive and self-tuning control, and real-time control applications.




Dynamical Systems, Wave-Based Computation and Neuro-Inspired Robots


Book Description

This volume is a special Issue on "Dynamical Systems, Wave based computation and neuro inspired robots'^ based on a Course carried out at the CISM in Udine (Italy), the last week of September, 2003. From the topics treated within that Course, several new ideas were f- mulated, which led to a new kind of approach to locomotion and p- ception, grounded both on biologically inspired issues and on nonlinear dynamics. The Course was characterised by a high degree of multi disciplinarity. In fact, in order to conceive, design and build neuro inspired machines, it is necessary to deeply scan into different d- ciplines, including neuroscience. Artificial Intelligence, Biorobotics, Dynamical Systems theory and Electronics. New types of moving machines should be more closely related to the biological rules, not discarding the real implementation issues. The recipe has to include neurobiological paradigms as well as behavioral aspects from the one hand, new circuit paradigms, able of real time control of multi joint robots on the other hand. These new circuit paradigms are based on the theory of complex nonlinear dynamical systems, where aggregates of simple non linear units into ensembles of lattices, have the pr- erty that the solution set is much richer than that one shown by the single units. As a consequence, new solutions ^'emerge'\ which are often characterized by order and harmony.




Natural & Artificial Parallel Computation


Book Description

The volume begins with processing in biological organisms, moves through interactions between processing in biology and computer science, and ends with massively parallel computing. It contains articles by scientists exploring the modeling of biological systems on computers and computer designers interested in exploiting massive numbers of computing elements in parallel.




Synaptic Plasticity for Neuromorphic Systems


Book Description

One of the most striking properties of biological systems is their ability to learn and adapt to ever changing environmental conditions, tasks and stimuli. It emerges from a number of different forms of plasticity, that change the properties of the computing substrate, mainly acting on the modification of the strength of synaptic connections that gate the flow of information across neurons. Plasticity is an essential ingredient for building artificial autonomous cognitive agents that can learn to reliably and meaningfully interact with the real world. For this reason, the neuromorphic community at large has put substantial effort in the design of different forms of plasticity and in putting them to practical use. These plasticity forms comprise, among others, Short Term Depression and Facilitation, Homeostasis, Spike Frequency Adaptation and diverse forms of Hebbian learning (e.g. Spike Timing Dependent Plasticity). This special research topic collects the most advanced developments in the design of the diverse forms of plasticity, from the single circuit to the system level, as well as their exploitation in the implementation of cognitive systems.










Introduction to Neural Architecture Search


Book Description

"Introduction to Neural Architecture Search: Optimizing AI Models" delves into the transformative realm of automating neural network design. As the AI landscape advances rapidly, NAS has emerged as an essential field, streamlining the creation of efficient, high-performance models. This book offers a comprehensive examination of NAS's foundational concepts, cutting-edge algorithms, and real-world applications, making it an indispensable resource for those seeking to deepen their understanding of AI model optimization. Designed to cater to a diverse audience, from beginners to seasoned practitioners, the book meticulously explores each facet of NAS, from the underlying neural network principles to intricate evaluation methods. Readers will gain insights into popular NAS algorithms, tools, and frameworks, complemented by case studies illuminating NAS's practical impact. As it addresses current challenges and future directions, the book empowers readers to navigate the evolving landscape of NAS, equipping them with the knowledge needed to spearhead innovative AI solutions.