Browsing DSP Publications by Type "Report"
Now showing items 120 of 45

The 2nuSVM: A CostSensitive Extension of the nuSVM
(20051201)Standard classification algorithms aim to minimize the probability of making an incorrect classification. In many important applications, however, some kinds of errors are more important than others. In this report we review costsensitive extensions of standard support vector machines (SVMs). In particular, we describe costsensitive extensions of ... 
Adaptive Wavelet Transforms via Lifting
(19990115)This paper develops new algorithms for adapted multiscale analysis and signal adaptive wavelet transforms. We construct our adaptive transforms with the <i>lifting scheme</i>, which decomposes the wavelet transform into prediction and update stages. We adapt the prediction stage to the signal structure and design the update stage to preserve the ... 
Algorithms for Optimal Numerical Quadrature Based on Signal Class Models
(19791101)A framework is presented for constructing various types of numerical quadrature algorithms which take into account the apriori known or estimated properties of the signal being processed. This is done by appropriately modeling the signal class to which such a signal belongs. Both linear and nonlinear signal class models are considered and wide ... 
Analysis of the DCS onestage Greedy Algorothm for Common Sparse Supports
(20051101)Analysis of the DCS onestage Greedy Algorothm for Common Sparse Supports 
Application of a Frequency Domain Prony Method to Wide Bandwidth Radar Signature Classification
(19790920)A frequency domain Prony approach is presented for extracting features of return signals from targets illuminated by wide bandwidth (short pulse) radar. Theoretical details pertaining to this approach are described in a separate paper. The features mentioned above consist of the relative delays and reflection coefficients pertaining to scattering ... 
Compressing Piecewise Smooth Multidimensional Functions Using Surflets: RateDistortion Analysis
(20040301)Discontinuities in data often represent the key information of interest. Efficient representations for such discontinuities are important for many signal processing applications, including compression, but standard Fourier and wavelet representations fail to efficiently capture the structure of the discontinuities. These issues have been most notable ... 
Design of Linear Phase Cosine Modulated Filter Banks for Subband Image Compression
(19940115)Wavelet methods give a flexible alternative to Fourier methods in nonstationary signal analysis. The concept of bandlimitedness plays a fundamental role in Fourier analysis. Since wavelet theory replaces frequency with scale, a natural question is whether there exists a useful concept of scalelimitedness. Obvious definitions of scalelimitedness ... 
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 be much smaller than the number of Nyquist rate samples. Interestingly, it has been shown that random projections are a satisfactory ... 
Digital Signal Processing Structures: Block and Multidemensional Formulation and Distributed Arithmetic
(19780120)In this report we will consider a special class of digital filter structure; and by structure we mean the particular arrangement and sequence of arithmetic and storage operations to realize a desired signal processing function. The more conventional structures consist of an interconnection of arithmetic operations such as addition and multiplication ... 
Distributed Multiscale Data Analysis and Processing for Sensor Networks
(20050201)While multiresolution data analysis, processing, and compression hold considerable promise for sensor network applications, progress has been confounded by two factors. First, typical sensor data are irregularly spaced, which is incompatible with standard wavelet techniques. Second, the communication overhead of multiscale algorithms can become ... 
Edge Characteristics in WaveletBased Image Coding
(20010420)Accurate prediction of wavelet coefficients relies on an understanding of the phase effects of edge alignment. This research examines techniques for uncovering edge information based on the available coefficients. These techniques are evaluated in the context of reconstructing an image from quantized wavelet coefficients. A predictor is described ... 
The Effect of Intersymbol Interference on the Performance of a Digital FM System
(19741020)The error performance of a digital FM system is studied in the presence of additive Gaussian noise. The digital system considered is a conventional one employing a voltagecontrolled oscillator as the modulator and a limiterdiscriminator followed by a lowpass filter as the demodulator. The notion of 
Efficient Solution of a ToeplitzPlusHankel Coefficient Matrix System of Equations
(19800501)Frequently in signal processing one is faced with situations where a large system of linear equations, with a Toeplitz or a Hankel coefficient matrix, needs to be solved. One efficient way of solving these kinds of equations is by Levinson recursion. The Levinson recursion does not require explicit storage of the Toeplitz (or Hankel) coefficient ... 
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 DNA to the stock market. Synthesis algorithms play a key role by providing the feedstock of data necessary for running complex ... 
A FourierProny Tauberian Approach to the Analysis of a Mixture of Delayed Signals
(19790920)Let x and y be signals (i.e. realvalued functions of time) of finite duration and energy. In the present paper, we develop a frequency domain Prony approach for interpolating, or in general, approximating y(t) by .... 
Improving the Resolution of Bearing in Passive Sonar Arrays by Eigenvalue Analysis
(19810801)A method of improving the bearingresolving capabilities of a passive array is discussed. This method is an adaptive beamforming method, having many similarities to the minimum energy approach. The evaluation of energy in each steered beam is preceded by an eigenvalueeigenvector analysis of the emperical correlation matrix. Modification of the ... 
Magnitude Weighting and Time Segmentation for PhaseOnly Reconstruction of Signals
(19810401)Phaseonly reconstruction of signals and its application to blinddeconvolution were introduced recently by Oppenheim, and by Hayes, et.al. In this report, we briefly present another description of this phaseonly reconstruction, propose a new magnitude weighted reconstruction and show how these ideas can be applied to the deconvolution of segmented data. 
A Markov Chain Analysis of Blackjack Strategy
(20040701)Blackjack receives considerable attention from mathematicians and entrepreneurs alike, due to its simple rules, its inherent random nature, and the abundance of "prior" information available to an observant player. Many attempts have been made to propose cardcounting systems that exploit such information to the player's advantage. Because blackjack ... 
Multiresolution Intensity Estimation of Piecewise Linear Poisson Processes
(20010420)Given observations of a onedimensional piecewise linear, lengthM Poisson intensity function, our goal is to estimate both the partition points and the parameters of each segment. In order to determine where the breaks lie, we develop a maximum penalized likelihood estimator based on informationtheoretic complexity penalization. We construct a ... 
A Multiscale Data Representation for Distributed Sensor Networks: Proofs of Basis Characteristics and Error Bounds
(20040901)Provides proofs of Parseval tightframe membership and approximation properties for the basis proposed in "A Multiscale Data Representation for Distributed Sensor Networks" by R. Wagner, S. Sarvotham, and R. Baraniuk (ICASSP 2005).