Signal-to-Symbol Transformation: HASP/SIAP Case Study
1982; Association for the Advancement of Artificial Intelligence; Volume: 3; Issue: 2 Linguagem: Inglês
10.1609/aimag.v3i2.368
ISSN2371-9621
AutoresH. Penny Nii, Edward A. Feigenbaum, John J. Anton,
Tópico(s)Neural Networks and Applications
ResumoArtificial intelligence is that part of computer science that concerns itself with concepts and methods of symbolic inference and symbolic representation of knowledge. Its point of departure -- it's most fundamental concept -- is what Newell and Simon called (in their Turing Award Lecture) the physical symbol system. But within last fifteen years, it has concerned itself also with signals -- with interpretation or understanding of signal data. AI researchers have discussed signal-to symbol transformations, and their programs have shown how appropriate use of symbolic manipulations can be of great use in making signal processing more effective and efficient. Indeed, programs for signal understanding have been fruitful, powerful, and among most widely recognized of AI's achievements.
Referência(s)