Ears are an emergent biometric accruing application advantages including no requirement for subject contact and acquisition without demand. To recognize a subject's ear, we aim to extract a characteristic vector from a human ear image that may subsequently be used to identify or confirm the identity of the owner. Towards this end, a novel force field transformation and potential well extraction...

The problem of consistently estimating the sparsity pattern of a vector β∗ ∈ R based on observations contaminated by noise arises in various contexts, including subset selection in regression, structure estimation in graphical models, sparse approximation, and signal denoising. We analyze the behavior of l1-constrained quadratic programming (QP), also referred to as the Lasso, for recovering th...

This paper describes a system for determining intervals of “high” and “low” signal-to-noise ratios when the desired signal and interfering noise arise from distinct spatial regions. The correlation coefficient between two microphone signals serves as the decision variable in a hypothesis test. The system has three parameters: center frequency and bandwidth of the bandpass filter that prefilters...

Quantization index modulation (QIM) is a powerful hostinterference rejecting method for data hiding. This paper applies QIM to one-bit watermarking and proposes a simple but powerful watermark detector. We derive lower bounds on the error exponents for the detector under a quadratic distortion constraint for the watermarker and additive white Gaussian noise attacks. These bounds are independent...

The feedback capacity of the stationary Gaussian additive noise channel has been open, except for the case where the noise is white. Here we obtain the closed-form feedback capacity of the first-order moving average additive Gaussian noise channel. Specifically, the channel is given by Yi = Xi +Zi, i = 1, 2, . . . , where the input {Xi} satisfies a power constraint and the noise {Zi} is a first...

This summary will briefly describe some recent results in random matrix theory and their applications. 1 Motivation 1.1 Multiple Antenna Gaussian Channels 1.1.1 The deterministic case Consider a gaussian channel with t transmitting and r receiving antennas. The received vector y ∈Cr will depend on the transmitted vector x ∈Ct by y = Hx+n where H is an rxt complex matrix of gains and n is a vect...

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...

Recent results have shown that structured codes can be used to construct good channel codes, source codes and physical layer network codes for Gaussian channels. For Gaussian channels with secrecy constraints, however, efforts to date rely on random codes. In this work, we advocate that structured codes are useful for providing secrecy, and show how to compute the secrecy rate when structured c...

The canny edge detection technique is a multi-stage algorithm which is an optimal edge detection technique. But it removes noise in an image using Gaussian filter to become insensitive to noise. The Gaussian filter smoothes even the edges in the images so that the through put is decreased. That is some of the true edges may be missed and false edges may appear in the edge detection. We propose ...