Lattice coding and decoding have been shown to achieve the capacity of the additive white Gaussian noise (AWGN) channel. This was accomplished using a minimum mean-square error scaling and randomization to transform the AWGN channel into a modulo-lattice additive noise channel of the same capacity. It has been further shown that when operating at rates below capacity but above the critical rate...

This paper deals with denoising of density images with bad Poisson statistics (low count rates), where the reconstruction of the major structures seems the only reasonable task. Obtaining the structures with sharp edges can also be a prerequisite for further processing, e.g. segmentation of objects. A variety of approaches exists in the case of Gaussian noise, but only a few in the Poisson case...

Time-series prediction is important in physical and financial domains. Pattern recognition techniques for time-series prediction are based on structural matching of the current state of the time-series with previously occurring states in historical data for making predictions. This paper describes a Pattern Modelling and Recognition System (PMRS) which is used for forecasting benchmark series a...

NASA Tech Briefs, November 2010 yield this behavior. Previous work on mean-square error characterization for ML estimators has predominantly focused on additive Gaussian noise. This work demonstrates that the discrete nature of the Poisson noise process leads to a distinctly different error behavior. This work was done by Baris I. Erkmen and Bruce E. Moision of Caltech for NASA’s Jet Propulsion...

NASA Tech Briefs, November 2010 yield this behavior. Previous work on mean-square error characterization for ML estimators has predominantly focused on additive Gaussian noise. This work demonstrates that the discrete nature of the Poisson noise process leads to a distinctly different error behavior. This work was done by Baris I. Erkmen and Bruce E. Moision of Caltech for NASA’s Jet Propulsion...

T paper presents a new fast-pivoting algorithm that computes the n Gittins index values of an n-state bandit—in the discounted and undiscounted cases—by performing 2/3 n3 +O n2 arithmetic operations, thus attaining better complexity than previous algorithms and matching that of solving a corresponding linearequation system by Gaussian elimination. The algorithm further applies to the problem of...

A new threshold is presented for better estimating a signal by sparse transform and soft thresholding. This threshold derives from a non-parametric statistical approach dedicated to the detection of a signal with unknown distribution and unknown probability of presence in independent and additive white Gaussian noise. This threshold is called the detection threshold and is particularly appropri...

A modified spatially adaptive denoising algorithm for a single image corrupted by Gaussian noise is proposed in this paper. The proposed algorithm use local statistics of a selected window i.e. by defining local weighted mean, local weighted activity and local maximum. These local statistics are used to detect the noise in the image then a modified Gaussian filter is used for noise suppression....

A central problem in sensor array processing is the localization of multiple sources and the reception of the signals emitted by those sources. Many approaches have been studied for this problem when the additive noise in the sensor array data is modeled with a Gaussian distribution. However, the schemes designed for Gaussian noise typically perform very poorly when the noise is non-Gaussian. A...

Form document structure analysis is an intrinsic technique. However, It has fundamental problems because interruptions of lines and noise cause low-quality form images. This paper focuses on connecting disappeared comer patterns. Our method has two stages for making correct connections, noise elimination, in which lines whose two end points meet no other lines are eliminated and object line sel...