Browsing by Author "Yen, WC"

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A new compact neuron-bipolar cellular neural network structure with adjustable neighborhood layers and high integration level
(1999)
Yen, WC
;
Wu, CY
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
A new compact structure called the neuron-bipolar cellular neural network is proposed and analyzed. In the new structure, the parasitic PNP bipolar junction transistor in the CMOS process is used to implement the neuron whereas the coupling MOS resistor is used to realize the synapse weights among various neurons. It has the advantages of compact structure and small chip size. The neuron-bipolar CNN with single neighborhood layer r=1 has been successfully applied to the noise removing operation on images. Moreover, the proposed neuron-bipolar CNN can easily realize the multi-layer neighborhood structure. Thus the proposed neuron-bipolar CNN has a great potential in the VLSI implementation of neural network.
A new compact neuron-bipolar junction transistor (nu BJT) cellular neural network (CNN) structure with programmable large neighborhood symmetric templates for image processing
(2001-01-01)
Wu, CY
;
Yen, WC
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
Based on the basic device physics of the neuron-bipolar junction transistor (nu BJT), a new compact cellular neural network (CNN) structure called the nu BJT CNN is proposed and analyzed. In the nu BJT CNN, both nu BJT and lambda bipolar transistor realized by parasitic p-n-p BJTs in the CMOS process are used to implement the neuron whereas the coupling MOS resistors are used to realize the symmetric synapse weights among various neurons. Thus it has the advantages of small chip area and high integration capability, Moreover, the proposed symmetric nu BJT CNN can be easily designed to achieve large neighborhood without extra interconnection. By adding a metal-layer optical window to the nu BJT, the nu BJT can be served as the phototransistor, and the nu BJT CNN can receive optical images as initial state inputs or external inputs. The correct functions of the nu BJT CNNs in noise removal, hole filling, and erosion have been successfully verified in HSPICE simulation. An experimental chip containing a 32 x 32 nu BJT CNN and a 16 x 16 nu BJT CNN with phototransistor design, has been designed and fabricated in 0.6-mum single-poly triple-metal n-well CMOS technology. The fabricated chips have the cell state transition time of 0.8 mus and the static power consumption of 60 muW/cell. The area density can be as high as 1270 cells/mm(2). The measurement results have also confirmed the correct functions of the proposed nu BJT CNNs.
In the blink of a silicon eye
(2001-05-01)
Cheng, CH
;
Wu, CY
;
Sheu, B
;
Lin, LJ
;
Huang, KH
The design of neuron-bipolar junction transistor (vBJT) cellular neural network (CNN) structure with multi-neighborhood-layer templates
(2000)
Yen, WC
;
Wu, CY
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
A compact and efficient neuron-bipolar junction transistor (vBJT) cellular neural network(CNN) structure with multi-neighborhood-layer templates is proposed and analyzed Using the proposed structure, the coefficients ol the templates with two neighborhood layers are fully realizable. But those with more than two neighborhood layers ore constrained. As the demonstrative examples on the applications of the proposed vBJT CNNs, the functions of both de-blurring and muller-lyer arrowhead illusion functions have been successfully realized and verified by HSPICE simulation.