Resource allocation using a constraint optimizing adaptive neural network

✍ Scribed by George W. Earle; Harold Szu

• Publisher: Elsevier Science
• Year: 1988
• Tongue: English
• Weight: 86 KB
• Volume: 1
• Category: Article
• ISSN: 0893-6080
• DOI: 10.1016/0893-6080(88)90459-5

✦ Synopsis

Resource/equipment allocation applications are becoming increasingly difficult to manage because of the routing/control complexity and contention conflicts, i.e. the amount of equipment operating simultaneously. The technical diversity of this equipment is also growing. Architectures that once included many analog devices are steadily converting to digital hardware and software. Conventional, von Neuman based computers are often used to handle this allocation task. Unfortunately, von Neuman based static control designs inhibit dynamic allocation and re-configuration demanded by difficult, emerging requirements; e.g., in ELINT systems' automated built-in test equipment (BITE)]decreasing allocation response time and NCUBETM-Iike computing architectures.