CHAPTER 7 ARTIFICIAL NEURAL NETWORK APPLICATIONS 67 SUMMARY 67 TECHNOLOGY 67 ARTIFICIAL NEURAL NETWORKS 67 MEMRISTOR-BASED ARTIFICIAL NEURAL NETWORKS 68 RECENT DEVELOPMENTS 69 IBM INTRODUCES DIGITAL NEUROSYNAPTIC CORE 69 INTEL REVEALS NEUROMORPHIC CHIP DESIGN 70 PANASONIC DEVELOPS LOW ENERGY CONSUMPTION CIRCUIT FOR NEURAL NETWORK SYSTEMS 70 NEUROCOMPUTER
PROGRAMMING SOFTWARE ECOSYSTEM 70 MEMRISTORS TO BOOST IMAGE PROCESSING 71 APPLICATIONS 71 MARKET PROJECTIONS 71 TABLE 8 PROJECTED MARKET FOR MEMRISTOR NEUROMORPHIC CHIPS, THROUGH 2023 ($ MILLIONS) 72
It appears that Japan was the first to recognize the enormous potential of neural networks, and some European sources claim that this country is already working on a second-generation neurocomputer.
The drawback is that the solution offered by the neurocomputer cannot be as exact as the human-written version because, after all, it represents merely an approximation, a near-optimum solution.
TECHNOLOGIES 41 GENERAL PRINCIPLES 41 PHYSICAL ANNS 42 Memristive Neural Networks 42 Other Developments 44 IBM Introduces Digital Neurosynaptic Core 44 Intel Reveals Neuromorphic Chip Design 44 Panasonic Develops Low Energy Consumption Circuit for Neural Network Systems 45 Neurocomputer Programming Software Ecosystem 45 Memristors Boost Image Processing 46 SOFTWARE-BASED ANNS 46 APPLICATIONS 46 BANKING AND FINANCE 46 TABLE 3 REPORTED APPLICATIONS OF ANNS IN FINANCE AND ACCOUNTING 47 DEFENSE AND PUBLIC SAFETY 48 Defense 48 Public Safety 49 Law Enforcement 49
Bayesian Networks 30 HEURISTIC SYSTEMS 31 APPLICATIONS 31 AUTOMATIC FLIGHT CONTROL SYSTEMS 32 MEDICINE 32 Workflow Integration 33 FINANCIAL ANALYSIS 33 Expert Systems for Financial Analysis of Firms 34 Expert Systems for Analyzing the Causes of Successful or Unsuccessful Business Development 34 Expert Systems for Market Analysis 34 Expert Systems for Acquiring Knowledge in a Subfield of Finance 34 GEOLOGY 34 CHEMISTRY 35 METEOROLOGY 36 OTHER APPLICATIONS 37 MARKETS 37 TABLE 2 GLOBAL MARKET FOR EXPERT SYSTEMS, THROUGH 2024 ($ MILLIONS) 38 CHAPTER 6 NEURAL COMPUTERS 40 DEFINITION, GENERAL DESCRIPTION AND PROPERTIES 40 BIOLOGICAL NEUROCOMPUTERS 40 ARTIFICIAL NEURAL NETWORKS 40
A "controller" built into the neurocomputer then determined whether there was significant agreement between the three layers and, if agreement was reached, rendered a response.
Neurocomputers are a breed of rapidly developing hardware on which artificial neural networks are trained to solve problems.
The prototype chip is also a step toward neurocomputers.
It will take 10 to 20 years before the method can be used to make neurocomputers in the lab.
The two main categories consist of neurocomputers
based on standard integrated circuits and ASIC.
Robert Hecht-Nielsen, inventor of one of the earliest neurocomputers
, defines a neural network as a computing system made up of a number of simple, highly interconnected processing elements which process information by their dynamic state responses to external inputs (Caudill |8~).
Such hybrid machines are indeed beginning to appear under the label of neurocomputers