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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

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The Mod 2 Neurocomputer system design.

M L Mumford¹, D K Andes, L L Kern

¹US Naval Weapons Center, China Lake, CA.

IEEE Transactions on Neural Networks

|January 1, 1992

Summary

This summary is machine-generated.

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The Mod 2 Neurocomputer utilizes a hierarchical architecture for parallel processing of real-time image data. This advanced neural network system supports various processing paradigms and data transfer requirements.

Area of Science:

Neurocomputing
Artificial Intelligence
Computer Engineering

Background:

The Mod 2 Neurocomputer is an advancement in neurocomputing systems developed at the Naval Air Warfare Center Weapons Division.
It features a layered hierarchical architecture integrating individual neural networks as subsystems.

Purpose of the Study:

To describe the Mod 2 Neurocomputer system architecture and its design principles.
To detail the implementation strategy for supporting parallel processing of image data at real-time rates.

Main Methods:

The system employs a layered hierarchical architecture with individual neural networks as subsystems.
Key design concepts include frame-based data representation, a versatile interconnect design, and a neuroprocessing block.
Implementation is based on the Intel 80170NX neural network processor.

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Main Results:

The Mod 2 supports parallel processing of image data at sensor (real-time) rates.
It accommodates various data transfer requirements, including parallel pathways and feedback loops.
Demonstrates implementation strategies for neural substructures like multilayer perceptrons and spatiotemporal image processing.

Conclusions:

The Mod 2 Neurocomputer provides a robust platform for real-time image processing using neural networks.
Its architecture and design facilitate the implementation of diverse neural network paradigms and multifunction processing systems.