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Jeffrey L. Krichmar

Researcher at University of California, Irvine

Publications -  182
Citations -  5783

Jeffrey L. Krichmar is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Spiking neural network & Neuromorphic engineering. The author has an hindex of 35, co-authored 169 publications receiving 4981 citations. Previous affiliations of Jeffrey L. Krichmar include George Mason University & Krasnow Institute for Advanced Study.

Papers
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Journal ArticleDOI

Evolutionary robotics: The biology, intelligence, and technology of self‐organizing machines

TL;DR: A new book enPDFd evolutionary robotics the biology intelligence and technology of self organizing machines intelligent robotics and autonomous agents series to read.
Proceedings Article

A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors

TL;DR: This paper demonstrates an efficient, biologically realistic, large-scale SNN simulator that runs on a single GPU, and presents a collection of new techniques related to parallelism extraction, mapping of irregular communication, and network representation for effective simulation of SNNs on GPUs.
Journal ArticleDOI

Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: a simulation study

TL;DR: It is reported for the first time that differences in dendritic structure within the same morphological class can have a dramatic influence on the firing rate and firing mode (spiking versus bursting and type of bursting).
Journal ArticleDOI

2009 Special Issue: A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors

TL;DR: In this article, the authors demonstrate an efficient, biologically realistic, large-scale SNN simulator that runs on a single GPU, which includes Izhikevich spiking neurons, detailed models of synaptic plasticity and variable axonal delay.
Journal ArticleDOI

The Neuromodulatory System: A Framework for Survival and Adaptive Behavior in a Challenging World

TL;DR: It is proposed that principles of the neuromodulatory system could provide a framework for controlling artificial agents that may improve current artificial agent behavior.