Publications related to Piecewise uniform switched vector quantization of the memoryless two-dimensional Laplace source

Subthreshold Current-Mode Delta-Sigma Quantizer with 3-Decade Scalable Sampling Rate and pico-Ampere Range Resolution

A current-mode

\Delta\Sigma

analog-to-digital data converter (ADC) for biomedical readout front-end systems is being presented. The core of this circuit is a current-controlled ring oscillator (CCO) whose oscillation frequency is proportional to the inpu ...

2010

The SURE-LET approach to image denoising

Florian Luisier

Denoising is an essential step prior to any higher-level image-processing tasks such as segmentation or object tracking, because the undesirable corruption by noise is inherent to any physical acquisition device. When the measurements are performed by phot ...

EPFL2010

Spectral Noise Shaping: Improvements in Speech/Audio Codec Based on Linear Prediction in Spectral Domain

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy

Audio coding based on Frequency Domain Linear Prediction (FDLP) uses auto-regressive models to approximate Hilbert envelopes in frequency sub-bands. Although the basic technique achieves good coding efficiency, there is a need to improve the reconstructed ...

2008

Spectral Noise Shaping: Improvements in Speech/Audio Codec Based on Linear Prediction in Spectral Domain

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy

Audio coding based on Frequency Domain Linear Prediction (FDLP) uses auto-regressive models to approximate Hilbert envelopes in frequency sub-bands. Although the basic technique achieves good coding efficiency, there is a need to improve the reconstructed ...

IDIAP2008

Monte-Carlo SURE: A Black-Box Optimization of Regularization Parameters for General Denoising Algorithms

Michaël Unser, Thierry Blu, Sathish Ramani

We consider the problem of optimizing the parameters of a given denoising algorithm for restoration of a signal corrupted by white Gaussian noise. To achieve this, we propose to minimize Stein's unbiased risk estimate (SURE) which provides a means of asses ...

IEEE2008

Blind optimization of algorithm parameters for signal denoising by Monte-Carlo sure

Michaël Unser, Thierry Blu, Sathish Ramani

We consider the problem of optimizing the parameters of an arbitrary denoising algorithm by minimizing Stein's Unbiased Risk Estimate (SURE) which provides a means of assessing the true mean-squared-error (MSE) purely from the measured data assuming that i ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008

Blind Optimization of Algorithm Parameters for Signal Denoising by Monte-Carlo SURE

Michaël Unser, Thierry Blu, Sathish Ramani

We consider the problem of optimizing the parameters of an arbitrary denoising algorithm by minimizing Stein's Unbiased Risk Estimate (SURE) which provides a means of assessing the true mean-squared-error (MSE) purely from the measured data assuming that i ...

IEEE2008

Low-power and low-voltage delta-sigma analog-to-digital converters for digital radio in standard CMOS technology

Nicola Scolari

The transceivers of a wireless sensor network (WSN) have to fulfill the low-power and low-voltage constraints. The WiseNET project has already proven that it is possible to design a receiver working at 1V and consuming less than 2mW. However this transceiv ...

EPFL2007

Oversampled A/D Conversion and Error-Rate Dependence of Non-Bandlimited Signals with Finite Rate of Innovation

Ivana Jovanovic

We study the problem of A/D conversion and error-rate dependence of a class of non-bandlimited signals which have a finite rate of innovation, particularly, a continuous periodic stream of Diracs, characterized by a finite set of time positions and weights ...

2006

Sampling in Practice: Is the Best Reconstruction Space Bandlimited?

Michaël Unser, Dimitri Nestor Alice Van De Ville, Sathish Ramani

Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some “shift-invariant” space, which may or may not be bandlimited. In this paper, we present some further justification for ...

IEEE2005

Piecewise uniform switched vector quantization of the memoryless two-dimensional Laplace source

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Subthreshold Current-Mode Delta-Sigma Quantizer with 3-Decade Scalable Sampling Rate and pico-Ampere Range Resolution

The SURE-LET approach to image denoising

Spectral Noise Shaping: Improvements in Speech/Audio Codec Based on Linear Prediction in Spectral Domain

Spectral Noise Shaping: Improvements in Speech/Audio Codec Based on Linear Prediction in Spectral Domain

Monte-Carlo SURE: A Black-Box Optimization of Regularization Parameters for General Denoising Algorithms

Blind optimization of algorithm parameters for signal denoising by Monte-Carlo sure

Blind Optimization of Algorithm Parameters for Signal Denoising by Monte-Carlo SURE

Low-power and low-voltage delta-sigma analog-to-digital converters for digital radio in standard CMOS technology

Oversampled A/D Conversion and Error-Rate Dependence of Non-Bandlimited Signals with Finite Rate of Innovation

Sampling in Practice: Is the Best Reconstruction Space Bandlimited?

Monte-Carlo SURE: A Black-Box Optimization of Regularization Parameters for General Denoising Algorithms

Subthreshold Current-Mode Delta-Sigma Quantizer with 3-Decade Scalable Sampling Rate and pico-Ampere Range Resolution

The SURE-LET approach to image denoising

Spectral Noise Shaping: Improvements in Speech/Audio Codec Based on Linear Prediction in Spectral Domain

Spectral Noise Shaping: Improvements in Speech/Audio Codec Based on Linear Prediction in Spectral Domain

Sampling in Practice: Is the Best Reconstruction Space Bandlimited?

Blind optimization of algorithm parameters for signal denoising by Monte-Carlo sure

Oversampled A/D Conversion and Error-Rate Dependence of Non-Bandlimited Signals with Finite Rate of Innovation

Low-power and low-voltage delta-sigma analog-to-digital converters for digital radio in standard CMOS technology

Blind Optimization of Algorithm Parameters for Signal Denoising by Monte-Carlo SURE