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JMLR
2006
389views more  JMLR 2006»
13 years 7 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
RTAS
2009
IEEE
14 years 2 months ago
Real-Time Video Surveillance over IEEE 802.11 Mesh Networks
In recent years, there has been an increase in video surveillance systems in public and private environments due to a heightened sense of security. The next generation of surveill...
Arvind Kandhalu, Anthony Rowe, Ragunathan Rajkumar...
HPCA
2008
IEEE
14 years 8 months ago
System level analysis of fast, per-core DVFS using on-chip switching regulators
Portable, embedded systems place ever-increasing demands on high-performance, low-power microprocessor design. Dynamic voltage and frequency scaling (DVFS) is a well-known techniq...
Wonyoung Kim, Meeta Sharma Gupta, Gu-Yeon Wei, Dav...
CASES
2005
ACM
13 years 9 months ago
Optimizing stream programs using linear state space analysis
Digital Signal Processing (DSP) is becoming increasingly widespread in portable devices. Due to harsh constraints on power, latency, and throughput in embedded environments, devel...
Sitij Agrawal, William Thies, Saman P. Amarasinghe
NCA
2007
IEEE
14 years 1 months ago
Implementing Atomic Data through Indirect Learning in Dynamic Networks
Developing middleware services for dynamic distributed systems, e.g., ad-hoc networks, is a challenging task given that such services deal with dynamically changing membership and...
Kishori M. Konwar, Peter M. Musial, Nicolas C. Nic...