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The CNN universal machine: an analogic array computer

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TLDR
The CNN universal machine is described, emphasizing its programmability as well as global and distributed analog memory and logic, high throughput via electromagnetic waves, and complex cells that may be used also for simulating a broad class of PDEs.
Abstract
A new invention, the cellular neural network (CNN) universal machine and supercomputer, is presented. This is the first algorithmically programmable analog array computer having real-time and supercomputer power on a single chip. The CNN universal machine is described, emphasizing its programmability as well as global and distributed analog memory and logic, high throughput via electromagnetic waves, and complex cells that may be used also for simulating a broad class of PDEs. Its implementation, the CNN universal chip, is also described, along with its use of a multichip supercomputer. Other types of hardware implementations are also briefly discussed. Details of the algorithmic aspects of the new type of analogic (analog logic) algorithms, as well as the analogic software (language, compiler, machine code, etc.) are explained, along with a brief description of the available CNN workstation for implementing and simulating these new concepts. A broad range of applications is reviewed, including neuromorphic computing, programmable physics, programmable chemistry, and programmable bionics. >

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Citations
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Blood vessel segmentation methodologies in retinal images - A survey

TL;DR: The aim of this paper is to review, analyze and categorize the retinal vessel extraction algorithms, techniques and methodologies, giving a brief description, highlighting the key points and the performance measures.
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Artificial neural networks in hardware: A survey of two decades of progress

TL;DR: This article presents a comprehensive overview of the hardware realizations of artificial neural network models, known as hardware neural networks (HNN), appearing in academic studies as prototypes as well as in commercial use.
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Neural Synaptic Weighting With a Pulse-Based Memristor Circuit

TL;DR: A pulse-based programmable memristor circuit for implementing synaptic weights for artificial neural networks is proposed, and both positive and negative multiplications are performed via a charge-dependent Ohm's law.
Journal ArticleDOI

Methods for image processing and pattern formation in Cellular Neural Networks: a tutorial

TL;DR: It is shown how generalizations of these templates can be used to design linear and nonlinear filters for image processing tasks such as low-pass filtering, time-varying spatial filtering, and fingerprint enhancement.
Journal ArticleDOI

Autonomous cellular neural networks: a unified paradigm for pattern formation and active wave propagation

TL;DR: This tutorial paper proposes a subclass of cellular neural networks having no inputs as a universal active substrate or medium for modeling and generating many pattern formation and nonlinear wave phenomena from numerous disciplines, including biology, chemistry, ecology, engineering, and physics.
References
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Book

Principles of Neural Science

TL;DR: The principles of neural science as mentioned in this paper have been used in neural networks for the purpose of neural network engineering and neural networks have been applied in the field of neural networks, such as:
Journal ArticleDOI

Cellular neural networks: theory

TL;DR: In this article, a class of information processing systems called cellular neural networks (CNNs) are proposed, which consist of a massive aggregate of regularly spaced circuit clones, called cells, which communicate with each other directly through their nearest neighbors.
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Cellular neural networks: applications

TL;DR: Examples of cellular neural networks which can be designed to recognize the key features of Chinese characters are presented and their applications to such areas as image processing and pattern recognition are demonstrated.
Journal ArticleDOI

Information Processing in the Primate Visual System: An Integrated Systems Perspective

TL;DR: The primate visual system contains dozens of distinct areas in the cerebral cortex and several major subcortical structures that are extensively interconnected in a distributed hierarchical network that contains several intertwined processing streams.
Journal ArticleDOI

Stimulus Specific Responses from Beyond the Classical Receptive Field: Neurophysiological Mechanisms for Local-Global Comparisons in Visual Neurons

TL;DR: The historical development of the evidence of response selectivity for visual stimuli presented beyond the CRF is traced; the anatomical pathways that sub serve these far-reaching surround mechanisms are examined; and the possible relationships between these mechanisms and perception are explored.
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