Hardware architecture of a neural network model simulating pattern recognition by the olfactory bulb

Neural Networks

Volumn 2, Issue 4, 1989, Pages 315-325

  Eisenberg, Joe ^a   Freeman, Walter J ^a   Burke, Brian ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Hardware; Multiplexing; Neural networks; Olfactory bulb; Oscillation

Indexed keywords

COMPUTER PROGRAMMING--ALGORITHMS; COMPUTER SYSTEMS, DIGITAL--PARALLEL PROCESSING; PATTERN RECOGNITION;

LEARNING ALGORITHMS; OLFACTORY BULB SIMULATION;

SYSTEMS SCIENCE AND CYBERNETICS;

EID: 0024866956     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/0893-6080(89)90040-3     Document Type: Article

References (25)

1. Bifurcation theory methods for programming static or periodic attractors and their bifurcation in dynamic neural networks
2. Pattern analysis of cortical evoked potential parameters during attention changes
3. Nonlinear gain mediating cortical stimulus-response relations
4. Nonlinear dynamics of paleocortex manifested in the olfactory EEG
5. Genesis of chaos in neural pattern recognition systems
6. Hardware simulation of brain dynamics in learning: SPOCK
7. Relation of olfactory bulb EEG to behavior: Time series analysis
8. Relation of olfactory EEG to behavior: factor analysis
9. Spatial EEG patterns, nonlinear dynamics and perception: The neo-Sherringtonian view
10. Central Pattern generating and recognizing in the olfactory bulb: A correlation learning rule
11. A CMOS associative memory chip
12. Chemical dependencies of learning in the rabbit olfactory bulb: Aquisition of the transient spatial-pattern changes depends on Norepinephrine
13. Neuronal circuitry in olfactory cortex: Anatomy and functional implications
14. Neurocomputing Picking the human brain
15. Neural networks and physical systems with emergent collective computational abilities
16. Real time imaging of evoked activity of local circuits of the olfactory bulb of salamander
17. A neurocomputer based on an analog-digital hybrid architecture
18. Recurrent excitation of secondary olfactory neurons: A possible mechanism for signal amplification
19. An artificial neural network integrated circuit based on MNOS/CCD principles
20. VLSI architectures for implementation of neural networks