Simulating neural network learning with TEST/NIL

Autor:	D. E. House
Rok vydání:	1989
Předmět:	Computer science business.industry Neural network learning General Medicine computer.software_genre Input language Test (assessment) Parallelism (grammar) Learning theory Pulse transmission Compiler Artificial intelligence Discrete event simulation business computer
Zdroj:	ACM SIGSIM Simulation Digest. 20:22-30
ISSN:	0163-6103
DOI:	10.1145/70256.70258
Popis:	TEST/NIL is a neural network learning simulation tool. TEST (Threshold Element Simulation Tool) is both an input language compiler and a simulation environment builder. NIL is the Network Input Language. TEST/NIL was designed to investigate biologically plausible learning theories at a level lower than that of cognitive psychology and higher than that of chemical pulse transmission. The discrete event simulation technique used by TEST/NIL is designed for possible optimization via parallelism. Appendices summarize the input language and provide a programming example.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b274d4a4797ba6d0a9e155e33a095a58 https://doi.org/10.1145/70256.70258 Zobrazit plný text záznamu