Title
Non-Refreshing Analog Neural Storage Tailored for On-Chip Learning
Abstract
In this research, we devised a new simple technique for statically holding analog weights, which does not require periodic refreshing. It further contains a mechanism to locally update the weights from the analog back-propagation signals for fast on-chip learning. In this circuit, the weight is stored as a 5-bit digital number, which controls the gates of five pass transistors allowing five binary-weighted (1,2,4,8,16) voltage references to integrate at a voltage adder. The output of the voltage adder is the analog weight. The 5-bit register is designed as an up/down counter so that every pulse on the up/down input will increase/decrease the weight by one level out of 32 possible levels. The learning circuit takes the analog graded error signal and generates two pulse streams for up/down counting depending on the sign of the error signal. The duration of the pulse stream is proportional to the magnitude of the error signal. This complete modular synaptic body (storage and learning technique) is appropriate for large scaleable analog VLSI neural networks because it handle recall and learning operations at the same speed with full parallelism.
Year
DOI
Venue
1998
10.1109/GLSV.1998.665220
Great Lakes Symposium on VLSI
Keywords
Field
DocType
voltage reference,error signal,large scaleable analog,analog weight,fast on-chip learning,analog graded error signal,pulse stream,analog back-propagation signal,non-refreshing analog neural storage,voltage adder,on-chip learning,statically holding analog weight,registers,adders,digital control,back propagation,very large scale integration,chip,neural networks,signal generators,neural network,vlsi,backpropagation
Analog device,Analog multiplier,Adder,Computer science,Voltage,Electronic engineering,Analog signal,Computer hardware,Backpropagation,Artificial neural network,Very-large-scale integration
Conference
ISSN
ISBN
Citations 
1066-1395
0-8186-8409-7
0
PageRank 
References 
Authors
0.34
1
3
Name
Order
Citations
PageRank
Bassem A. Alhalabi101.35
Qutaibah Malluhi221710.17
Rafic Ayoubi381.53