Sciweavers

908 search results - page 10 / 182
» Computational methodologies for modelling, analysis and simu...
Sort
View
APPINF
2003
13 years 9 months ago
Preventing Computational Chaos in Asynchronous Neural Networks
One of the primary advantages of artificial neural networks is their inherent ability to perform massively parallel, nonlinear signal processing. However, the asynchronous dynamics...
Jacob Barhen, Vladimir Protopopescu
DAC
1997
ACM
13 years 11 months ago
Power Supply Noise Analysis Methodology for Deep-Submicron VLSI Chip Design
This paper describes a new design methodology to analyze the on-chip power supply noise for high performance microprocessors. Based on an integrated package-level and chip-level p...
Howard H. Chen, David D. Ling
RECOMB
2008
Springer
14 years 8 months ago
High-Resolution Modeling of Cellular Signaling Networks
A central challenge in systems biology is the reconstruction of biological networks from high-throughput data sets. A particularly difficult case of this is the inference of dynami...
Michael Baym, Chris Bakal, Norbert Perrimon, Bonni...
JCNS
2000
165views more  JCNS 2000»
13 years 7 months ago
A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Analysis and an Application to Orientati
We explore a computationally efficient method of simulating realistic networks of neurons introduced by Knight, Manin, and Sirovich (1996) in which integrate-and-fire neurons are ...
Duane Q. Nykamp, Daniel Tranchina
PERVASIVE
2009
Springer
14 years 2 months ago
Methodologies for Continuous Cellular Tower Data Analysis
This paper presents novel methodologies for the analysis of continuous cellular tower data from 215 randomly sampled subjects in a major urban city. We demonstrate the potential of...
Nathan Eagle, John A. Quinn, Aaron Clauset