Browsing DSP Publications by Issue Date
Now showing items 120 of 508

Sparse Coding with Population Sketches
(20090713) 
Fast, Exact Synthesis of Gaussian and nonGaussian LongRangeDependent Processes
(20090415)1/f noise and statistically selfsimilar random processes such as fractional Brownian motion (fBm) and fractional Gaussian noise (fGn) are fundamental models for a host of realworld phenomena, from network traffic to ... 
A Theoretical Analysis of Joint Manifolds
(200901)The emergence of lowcost sensor architectures for diverse modalities has made it possible to deploy sensor arrays that capture a single event from a large number of vantage points and using multiple modalities. In many ... 
Tuning support vector machines for minimax and NeymanPearson classification
(20080819)This paper studies the training of support vector machine (SVM) classifiers with respect to the minimax and NeymanPearson criteria. In principle, these criteria can be optimized in a straightforward way using a costsensitive ... 
Singlepixel imaging via compressive sampling
(20080301) 
Multiscale random projections for compressive classification
(20070901)We propose a framework for exploiting dimensionreducing random projections in detection and classification problems. Our approach is based on the generalized likelihood ratio test; in the case of image classification, ... 
Minimax support vector machines
(20070801)We study the problem of designing support vector machine (SVM) classifiers that minimize the maximum of the false alarm and miss rates. This is a natural classification setting in the absence of prior information regarding ... 
Regression level set estimation via costsensitive classification
(20070601)Regression level set estimation is an important yet understudied learning task. It lies somewhere between regression function estimation and traditional binary classification, and in many cases is a more appropriate setting ... 
A simple proof of the restricted isometry property for random matrices
(20070118)We give a simple technique for verifying the Restricted Isometry Property (as introduced by Candès and Tao) for random matrices that underlies Compressed Sensing. Our approach has two main ingredients: (i) concentration ... 
Quantization of Sparse Representations
(20070116)Compressive sensing (CS) is a new signal acquisition technique for sparse and compressible signals. Rather than uniformly sampling the signal, CS computes inner products with randomized basis functions; the signal is then ... 
The smashed filter for compressive classification and target recognition
(20070101)The theory of compressive sensing (CS) enables the reconstruction of a sparse or compressible image or signal from a small set of linear, nonadaptive (even random) projections. However, in many applications, including ... 
Detection and estimation with compressive measurements
(20061101)The recently introduced theory of compressed sensing enables the reconstruction of sparse or compressible signals from a small set of nonadaptive, linear measurements. If properly chosen, the number of measurements can ... 
Multiscale Queuing Analysis
(20061001)This paper introduces a new multiscale framework for estimating the tail probability of a queue fed by an arbitrary traffic process. Using traffic statistics at a small number of time scales, our analysis extends the ... 
Coherent Multiscale Image Processing using Quaternion Wavelets
(20061001)The quaternion wavelet transform (QWT) is a new multiscale analysis tool for geometric image features. The QWT is a near shiftinvariant tight frame representation whose coefficients sport a magnitude and three phases: ... 
Random Projections of Smooth Manifolds
(20061001)Many types of data and information can be described by concise models that suggest each data vector (or signal) actually has â few degrees of freedomâ relative to its size N. This is the motivation for a variety of ... 
Measurements vs. Bits: Compressed Sensing meets Information Theory
(20060901)Compressed sensing is a new framework for acquiring sparse signals based on the revelation that a small number of linear projections (measurements) of the signal contain enough information for its reconstruction. The ... 
Truncated online arithmetic with applications to communication systems
(20060901)Truncation and saturation in digitprecision are very important and common operations in embedded system design for bounding the required finite precision and for areatimepower savings. In this paper, we present the use ... 
Learning minimum volume sets with support vector machines
(20060901)Given a probability law P on ddimensional Euclidean space, the minimum volume set (MVset) with mass beta , 0 < beta < 1, is the set with smallest volume enclosing a probability mass of at least beta. We examine the use ... 
Development of Digital Signal Processor controlled Quantum Cascade Laser based Trace Gas Sensor Technology
(20060801)This work reports the design and integration of a custom digital signal processor (DSP) system into a pulsed quantum cascade laser (QCL) based trace gas sensor to improve its portability, robustness and operating performance. ... 
Robust Distributed Estimation Using the Embedded Subgraphs Algorithm
(20060801)We propose a new iterative, distributed approach for linear minimum meansquareerror (LMMSE) estimation in graphical models with cycles. The embedded subgraphs algorithm (ESA) decomposes a loopy graphical model into a ...