Abstract
Neurons are point process systems, in the sense that the inputs and output which are spike trains can be treated as point processes. System identification of a point process system has been studied mostly with single input. However, multiple input is required in many applications such as liquid state machines or neural prosthetics. We propose a simple multiple-input spike based adaptive filter which is based on an integrate-and-fire neuron model. The optimal closed solution is derived, and the performance is analyzed with respect to noise in various parameters and measurement. ©2007 IEEE.
Recommended Citation
I. Park et al., "A Closed Form Solution For Multiple-input Spike Based Adaptive Filters," IEEE International Conference on Neural Networks Conference Proceedings, pp. 2064 - 2068, article no. 4371276, Institute of Electrical and Electronics Engineers, Dec 2007.
The definitive version is available at https://doi.org/10.1109/IJCNN.2007.4371276
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
978-142441380-5
International Standard Serial Number (ISSN)
1098-7576
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Dec 2007
