Circuit Realization of a Programmable Neuron Transfer Function and Its Derivative

Como, Italy July 24-July 27

DOI Bookmark:

http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.860747

IEEE-INNS-ENNS International Joint Co ...

	This Article
	PURCHASE ARTICLE: $19 PDF HTML IEEE Xplore Subscribers
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Chun Lu Articles by Bingxue Shi

	ASCII Text	x
	Chun Lu, Bingxue Shi, "Circuit Realization of a Programmable Neuron Transfer Function and Its Derivative," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 4, pp. 4047, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4, 2000.

	BibTex	x
	@article{ 10.1109/IJCNN.2000.860747, author = {Chun Lu and Bingxue Shi}, title = {Circuit Realization of a Programmable Neuron Transfer Function and Its Derivative}, journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on}, volume = {4}, year = {2000}, issn = {1098-7576}, pages = {4047}, doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.860747}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on TI - Circuit Realization of a Programmable Neuron Transfer Function and Its Derivative SN - 1098-7576 SP EP A1 - Chun Lu, A1 - Bingxue Shi, PY - 2000 KW - Artificial Neural Networks (ANN) KW - CMOS analogue integrated circuits VL - 4 JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on ER -

Chun Lu, Tsinghua University

Bingxue Shi, Tsinghua University

In on-chip back-propagation learning neural networks, both a sigmoidal transfer function and its derivative are required. A simple CMOS analog neuron circuit that can realize both functions is proposed. The neuron is widely applicable because of its programmability. Based on this novel neuron a two-layer feedforward Artificial Neural Network (ANN) is designed. HSPICE simulation results have proved its ability to solve the XOR problem.

Index Terms:

Artificial Neural Networks (ANN), CMOS analogue integrated circuits

Citation:

Chun Lu, Bingxue Shi, "Circuit Realization of a Programmable Neuron Transfer Function and Its Derivative," ijcnn, vol. 4, pp.4047, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4, 2000

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.