Results 231 to 240 of about 20,110 (263)

Spectrogram enhancement algorithm: a soft thresholding-based approach

Ultrasound in Medicine & Biology, 1999
Enhancing the spectrogram by denoising the Doppler ultrasound signal is a preliminary step, and important for further processing. Because the spectrogram may be based on the short-time fast Fourier transform (FFT) of the Doppler ultrasound signal, whose power spectrum density is time-varying, traditional denoising algorithms that simply optimize the ...
B, Liu, Y, Wang, W, Wang
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Soft-decision threshold decoders

1979
Coding system designers are interested in threshold decoding for convolu-tional codes because of the hardware simplicity of the decoder. Unfortunately, majority-decision threshold decodable codes are sub-optimum, and this involves a loss in coding gain. In this paper a new method for implementing soft-decision threshold decoding is introduced, enabling
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Soft Error and Soft Delay Mitigation Using Dynamic Threshold Technique

IEEE Transactions on Nuclear Science, 2010
When designers try to address increasing power consumption reduction via optimizations, they need to be aware of the impact on single event robustness. In this work, we examined dynamic threshold MOS-based (DTMOS) schemes for their soft error and soft delay tolerance.
Selahattin Sayil, Nareshkumar B. Patel
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De-noising by modified soft-thresholding

IEEE APCCAS 2000. 2000 IEEE Asia-Pacific Conference on Circuits and Systems. Electronic Communication Systems. (Cat. No.00EX394), 2002
Based on the soft-thresholding, a new noise smoother is introduced in this letter. Since a new statistics is used to make the estimation, the proposed algorithm can smooth both white and impulsive noise efficiently.
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Soft Tissue Injury Threshold During Simulated Whiplash

Spine, 2004
A newly developed biofidelic whole cervical spine (WCS) model with muscle force replication (MFR) was subjected to whiplash simulations of varying intensity, and the resulting injuries were evaluated through changes in the intervertebral flexibility.To identify the soft tissue injury threshold based on the peak T1 horizontal acceleration and the ...
Shigeki, Ito, Paul C, Ivancic, Manohar M, Panjabi, Bryan W, Cunningham   +3 more
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On scaling of soft-thresholding estimator

Neurocomputing, 2016
LASSO is known to have a problem of excessive shrinkage at a sparse representation. To analyze this problem in detail, in this paper, we consider a positive scaling for soft-thresholding estimators that are LASSO estimators in an orthogonal regression problem.
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Hybrid threshold soft decision decoding algorithm

IEE Proceedings - Communications, 1994
A hybrid threshold soft decision decoding scheme which combines a Chase 2 algorithm with a bit-by-bit decision decoding algorithm is presented. For higher signal-to-noise ratios (SNRs), its behaviour is not inferior to that of the corresponding bit-by-bit decoding algorithm. This scheme can overcome the exponential increase of the test patterns used in
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Angle gather recovery using iterative soft thresholding

SEG Technical Program Expanded Abstracts 2014, 2014
Multi-dimensional angle gather construction for AVA and velocity analysis is a computational challenge due primarily to the accompanying increase in volume size which forces the gathers to be stored in a computationally more expensive memory level.
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Dynamic Threshold Technique for Soft Error and Soft Delay Mitigation

2016
The analysis in Chap. 8 had shown that decreasing threshold voltages increase the critical charge of logic circuits thus providing more robustness to radiation transients and soft delay effects. In a normal dynamic threshold MOS (DTMOS) scheme, the body-source junction is “forward biased” (at less than 0.6 V), forcing the threshold voltage to drop and ...
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Generalized Soft-Thresholding and Varying-coefficient Models

1997
We propose a new method for estimation of unknown functions within the generalized linear model framework. The estimator leads to an adaptive economical description of the results in terms of basis functions. Our proposal extends the soft--thresholding strategy from ordinary wavelet regression to generalized linear models and multiple predictor ...
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