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» Low power techniques for Motion Estimation hardware
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ANNPR
2006
Springer
13 years 9 months ago
A Convolutional Neural Network Tolerant of Synaptic Faults for Low-Power Analog Hardware
Abstract. Recently, the authors described a training method for a convolutional neural network of threshold neurons. Hidden layers are trained by by clustering, in a feed-forward m...
Johannes Fieres, Karlheinz Meier, Johannes Schemme...
ISCAS
2005
IEEE
112views Hardware» more  ISCAS 2005»
14 years 1 months ago
Field test results for low power bearing estimator sensor nodes
Pedro Julián, Andreas G. Andreou, Gert Cauw...
CGO
2005
IEEE
14 years 1 months ago
Compiler Managed Dynamic Instruction Placement in a Low-Power Code Cache
Modern embedded microprocessors use low power on-chip memories called scratch-pad memories to store frequently executed instructions and data. Unlike traditional caches, scratch-p...
Rajiv A. Ravindran, Pracheeti D. Nagarkar, Ganesh ...
DATE
2009
IEEE
242views Hardware» more  DATE 2009»
14 years 2 months ago
A high performance reconfigurable Motion Estimation hardware architecture
Motion Estimation (ME) is the most computationally intensive part of video compression and video enhancement systems. For the recently available high definition frame sizes and hi...
Ozgur Tasdizen, Halil Kukner, Abdulkadir Akin, Ilk...
ISLPED
2000
ACM
111views Hardware» more  ISLPED 2000»
14 years 2 days ago
Low power techniques and design tradeoffs in adaptive FIR filtering for PRML read channels
In this paper, we describe area and power reduction techniques for a low-latency adaptive finite-impulse response filter for magnetic recording read channel applications. Variou...
Khurram Muhammad, Robert B. Staszewski, Poras T. B...