Now showing items 1-60 of 508

  • Sparse Coding with Population Sketches 

    Dyer, Eva L.; Baraniuk, Richard G.; Johnson, Don H. (2009-07-13)
  • Fast, Exact Synthesis of Gaussian and nonGaussian Long-Range-Dependent Processes 

    Baraniuk, Richard; Crouse, Matthew (2009-04-15)
    1/f noise and statistically self-similar random processes such as fractional Brownian motion (fBm) and fractional Gaussian noise (fGn) are fundamental models for a host of real-world phenomena, from network traffic to ...
  • A Theoretical Analysis of Joint Manifolds 

    Davenport, Mark A.; Hegde, Chinmay; Duarte, Marco; Baraniuk, Richard G. (2009-01)
    The emergence of low-cost 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 Neyman-Pearson classification 

    Scott, Clayton D.; Baraniuk, Richard G.; Davenport, Mark A. (2008-08-19)
    This paper studies the training of support vector machine (SVM) classifiers with respect to the minimax and Neyman-Pearson criteria. In principle, these criteria can be optimized in a straightforward way using a cost-sensitive ...
  • Single-pixel imaging via compressive sampling 

    Duarte, Marco F.; Davenport, Mark A.; Takhar, Dharmpal; Laska, Jason N.; Sun, Ting; Kelly, Kevin F.; Baraniuk, Richard G. (2008-03-01)
  • Multiscale random projections for compressive classification 

    Duarte, Marco F.; Davenport, Mark A.; Wakin, Michael B.; Laska, Jason N.; Takhar, Dharmpal; Kelly, Kevin F.; Baraniuk, Richard G. (2007-09-01)
    We propose a framework for exploiting dimension-reducing 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 

    Davenport, Mark A.; Baraniuk, Richard G.; Scott, Clayton D. (2007-08-01)
    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 cost-sensitive classification 

    Scott, Clayton D.; Davenport, Mark A. (2007-06-01)
    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 

    Baraniuk, Richard G.; Davenport, Mark A.; DeVore, Ronald A.; Wakin, Michael B. (2007-01-18)
    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 

    Boufounos, Petros T.; Baraniuk, Richard G. (2007-01-16)
    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 

    Davenport, Mark A.; Duarte, Marco F.; Wakin, Michael B.; Laska, Jason N.; Takhar, Dharmpal; Kelly, Kevin F.; Baraniuk, Richard G. (2007-01-01)
    The theory of compressive sensing (CS) enables the reconstruction of a sparse or compressible image or signal from a small set of linear, non-adaptive (even random) projections. However, in many applications, including ...
  • Detection and estimation with compressive measurements 

    Baraniuk, Richard G.; Davenport, Mark A.; Wakin, Michael B. (2006-11-01)
    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 ...
  • Random Projections of Smooth Manifolds 

    Baraniuk, Richard G.; Wakin, Michael (2006-10-01)
    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 ...
  • Multiscale Queuing Analysis 

    Ribeiro, Vinay Joseph; Riedi, Rudolf H.; Baraniuk, Richard G. (2006-10-01)
    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 

    Chan, Wai Lam; Choi, Hyeokho; Baraniuk, Richard G. (2006-10-01)
    The quaternion wavelet transform (QWT) is a new multiscale analysis tool for geometric image features. The QWT is a near shift-invariant tight frame representation whose coefficients sport a magnitude and three phases: ...
  • Truncated on-line arithmetic with applications to communication systems 

    Rajagopal, Sridhar; Cavallaro, Joseph R. (2006-09-01)
    Truncation and saturation in digit-precision are very important and common operations in embedded system design for bounding the required finite precision and for area-time-power savings. In this paper, we present the use ...
  • Learning minimum volume sets with support vector machines 

    Davenport, Mark A.; Baraniuk, Richard G.; Scott, Clayton D. (2006-09-01)
    Given a probability law P on d-dimensional Euclidean space, the minimum volume set (MV-set) with mass beta , 0 < beta < 1, is the set with smallest volume enclosing a probability mass of at least beta. We examine the use ...
  • Measurements vs. Bits: Compressed Sensing meets Information Theory 

    Sarvotham, Shriram; Baron, Dror; Baraniuk, Richard G. (2006-09-01)
    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 ...
  • Development of Digital Signal Processor controlled Quantum Cascade Laser based Trace Gas Sensor Technology 

    So, Stephen; Wysocki, Gerard; Frantz, Patrick; Tittel, Frank K. (2006-08-01)
    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 

    Delouille, Veronique; Neelamani, Ramesh; Baraniuk, Richard G. (2006-08-01)
    We propose a new iterative, distributed approach for linear minimum mean-square-error (LMMSE) estimation in graphical models with cycles. The embedded subgraphs algorithm (ESA) decomposes a loopy graphical model into a ...
  • JPEG Compression History Estimation for Color Images 

    Neelamani, Ramesh; de Queiroz, Ricardo; Fan, Zhigang; Baraniuk, Richard G. (2006-06-01)
    We routinely encounter digital color images that were previously compressed using the Joint Photographic Experts Group (JPEG) standard. En route to the image's current representation, the previous JPEG compression's various ...
  • Sparse Signal Detection from Incoherent Projections 

    Davenport, Mark A.; Wakin, Michael B.; Duarte, Marco F.; Baraniuk, Richard G. (2006-05-01)
    The recently introduced theory of Compressed Sensing (CS) enables the reconstruction or approximation of sparse or compressible signals from a small set of incoherent projections; often the number of projections can be ...
  • Controlling False Alarms with Support Vector Machines 

    Davenport, Mark A.; Baraniuk, Richard G.; Scott, Clayton D. (2006-05-01)
    We study the problem of designing support vector classifiers with respect to a Neyman-Pearson criterion. Specifically, given a user-specified level alpha, 0 < alpha < 1, how can we ensure a false alarm rate no greater than ...
  • Random Projections of Signal Manifolds 

    Wakin, Michael; Baraniuk, Richard G. (2006-05-01)
    Random projections have recently found a surprising niche in signal processing. The key revelation is that the relevant structure in a signal can be preserved when that signal is projected onto a small number of random ...
  • Wavelet-Domain Approximation and Compression of Piecewise Smooth Images 

    Wakin, Michael; Romberg, Justin; Choi, Hyeokho; Baraniuk, Richard G. (2006-05-01)
    The wavelet transform provides a sparse representation for smooth images, enabling efficient approximation and compression using techniques such as zerotrees. Unfortunately, this sparsity does not extend to piecewise smooth ...
  • Random Filters for Compressive Sampling and Reconstruction 

    Baraniuk, Richard G.; Wakin, Michael; Duarte, Marco F.; Tropp, Joel A.; Baron, Dror (2006-05-01)
    We propose and study a new technique for efficiently acquiring and reconstructing signals based on convolution with a fixed FIR filter having random taps. The method is designed for sparse and compressible signals, i.e., ...
  • Universal Distributed Sensing via Random Projections 

    Wakin, Michael; Duarte, Marco F.; Baraniuk, Richard G.; Baron, Dror (2006-04-01)
    This paper develops a new framework for distributed coding and compression in sensor networks based on distributed compressed sensing (DCS). DCS exploits both intra-signal and inter-signal correlations through the concept ...
  • Faster Sequential Universal Coding via Block Partitioning 

    Baron, Dror; Baraniuk, Richard G. (2006-04-01)
    Rissanen provided a sequential universal coding algorithm based on a block partitioning scheme, where the source model is estimated at the beginning of each block. This approach asymptotically approaches the entropy at the ...
  • An Architecture for Distributed Wavelet Analysis and Processing in Sensor Networks 

    Wagner, Raymond; Baraniuk, Richard G.; Du, Shu; Johnson, David B.; Cohen, Albert (2006-04-01)
    Distributed wavelet processing within sensor networks holds promise for reducing communication energy and wireless bandwidth usage at sensor nodes. Local collaboration among nodes de-correlates measurements, yielding a ...
  • Representation and Compression of Multi-Dimensional Piecewise Functions Using Surflets 

    Chandrasekaran, Venkat; Wakin, Michael; Baron, Dror; Baraniuk, Richard G. (2006-03-01)
    We study the representation, approximation, and compression of functions in M dimensions that consist of constant or smooth regions separated by smooth (M-1)-dimensional discontinuities. Examples include images containing ...
  • Broadcast Detection Structures with Applications to Sensor Networks 

    Johnson, Don; Lexa, Michael (2006-03-01)
    Data broadcasting is potentially an effective and efficient way to share information in wireless sensor networks. Broadcasts offer energy savings over multiple, directed transmissions, and they provide a vehicle to exploit ...
  • Optimal Sampling Strategies for Multiscale Stochastic Processes 

    Ribeiro, Vinay Joseph; Riedi, Rudolf H.; Baraniuk, Richard G. (2006-01-15)
    In this paper, we determine which non-random sampling of fixed size gives the best linear predictor of the sum of a finite spatial population. We employ different multiscale superpopulation models and use the minimum ...
  • The 2nu-SVM: A Cost-Sensitive Extension of the nu-SVM 

    Davenport, Mark A. (2005-12-01)
    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 ...
  • The Dual-Tree Complex Wavelet Transform 

    Selesnick, Ivan W.; Baraniuk, Richard G.; Kingsbury, Nicholas G. (2005-11-01)
    The paper discusses the theory behind the dual-tree transform, shows how complex wavelets with good properties can be designed, and illustrates a range of applications in signal and image processing. The authors use the ...
  • Modeling wireless sensor and actuator networks using frame theory 

    Rozell, Chris; Johnson, Don (2005-11-01)
    Wireless sensor networks are often studied with the goal of removing information from the network as efficiently as possible. However, when the application also includes an actuator network, it is advantageous to determine ...
  • Analysis of the DCS one-stage Greedy Algorothm for Common Sparse Supports 

    Baron, Dror; Duarte, Marco F.; Wakin, Michael; Sarvotham, Shriram; Baraniuk, Richard G. (2005-11-01)
    Analysis of the DCS one-stage Greedy Algorothm for Common Sparse Supports
  • Distributed Compressed Sensing of Jointly Sparse Signals 

    Sarvotham, Shriram; Baron, Dror; Wakin, Michael; Duarte, Marco F.; Baraniuk, Richard G. (2005-11-01)
    Compressed sensing is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for reconstruction. In this paper we expand our theory for ...
  • Variable-Rate Universal Slepian-Wolf Coding with Feedback 

    Sarvotham, Shriram; Baron, Dror; Baraniuk, Richard G. (2005-11-01)
    Traditional Slepian-Wolf coding assumes known statistics and relies on asymptotically long sequences. However, in practice the statistics are unknown, and the input sequences are of finite length. In this finite regime, ...
  • Development of Japanese-language DSP Education Content in the Connexions Project 

    Frantz, Patrick; Yamada, Yoji (2005-10-01)
    Due to factors such as a small and fragmented market and rapid hardware development, the conventional textbook is inadequate for DSP lab education. Freely available open-content materials that enable and promote local ...
  • Coherent Image Processing using Quaternion Wavelets 

    Chan, Wai Lam; Choi, Hyeokho; Baraniuk, Richard G. (2005-08-01)
    We develop a quaternion wavelet transform (QWT) as a new multiscale analysis tool for geometric image features. The QWT is a near shift-invariant, tight frame representation whose coefficients sport a magnitude and three ...
  • The Multiscale Structure of Non-Differentiable Image Manifolds 

    Wakin, Michael; Donoho, David; Choi, Hyeokho; Baraniuk, Richard G. (2005-08-01)
    In this paper, we study families of images generated by varying a parameter that controls the appearance of the object/scene in each image. Each image is viewed as a point in high-dimensional space; the family of images ...
  • Distributed Wavelet Transform for Irregular Sensor Network Grids 

    Wagner, Raymond; Choi, Hyeokho; Baraniuk, Richard G.; Delouille, Veronique (2005-07-01)
    Wavelet-based distributed data processing holds much promise for sensor networks; however, irregular sensor node placement precludes the direct application of standard wavelet techniques. In this paper, we develop a new ...
  • JPEG Compression History Estimation for Color Images 

    Neelamani, Ramesh; de Queiroz, Ricardo; Fan, Zhigang; Dash, Sanjeeb; Baraniuk, Richard G. (2005-07-01)
    We routinely encounter digital color images that were previously JPEG-compressed. En route to the image's current representation, the previous JPEG compression's various settings&mdash;termed its JPEG compression history ...
  • Multiscale Approximation of Piecewise Smooth Two-Dimensional Function using Normal Triangulated Meshes 

    Jansen, Maarten; Baraniuk, Richard G.; Lavu, Sridhar (2005-07-01)
    Multiresolution triangulation meshes are widely used in computer graphics for representing three-dimensional(3-d) shapes. We propose to use these tools to represent 2-d piecewise smooth functions such as grayscale ...
  • Analyzing the robustness of redundant population codes in sensory and feature extraction systems 

    Rozell, Chris; Johnson, Don (2005-07-01)
    Sensorineural systems often use groups of redundant neurons to represent stimulus information both during transduction and population coding of features. This redundancy makes the system more robust to corruption in the ...
  • On Nearly Orthogonal Lattice Bases 

    Neelamani, Ramesh; Dash, Sanjeeb; Baraniuk, Richard G. (2005-07-01)
    We study "nearly orthogonal" lattice bases, or bases where the angle between any basis vector and the linear subspace spanned by the other basis vectors is greater than 60&deg;. We show that a nearly orthogonal lattice ...
  • Rate-constrained Relaying: A Model for Cooperation with Limited Relay Resources 

    Sabharwal, Ashutosh; Mitra, Urbashi (2005-06-01)
    In this paper, the impact of limited resources on achievable rates in relay channels is investigated. Resource limitation is modeled as a rate constraint, Rbar, which constrains the rate at which a relay can reliably ...
  • Examining methods for estimating mutual information in spiking neural systems 

    Rozell, Chris; Johnson, Don (2005-06-01)
    Mutual information enjoys wide use in the computational neuroscience community for analyzing spiking neural systems. Its direct calculation is difficult because estimating the joint stimulus-response distribution requires ...
  • Design of Adaptive Overlays for Multi-scale Communication in Sensor Networks 

    PalChaudhuri, Santashil; Kumar, Rajnish; Baraniuk, Richard G.; Johnson, David B. (2005-06-01)
    In wireless sensor networks, energy and communication bandwidth are precious resources. Traditionally, layering has been used as a design principle for network stacks; hence routing protocols assume no knowledge of the ...
  • Small-Time Scaling Behavior of Internet Backbone Traffic 

    Ribeiro, Vinay Joseph; Zhang, Zhi-Li; Moon, Sue; Diot, Christophe (2005-06-01)
    We perform an extensive wavelet analysis of Internet backbone traffic signals to observe and understand the causes of small-time (sub-seconds) scaling phenomena present in them. We observe that for a majority of the traffic ...
  • An FPGA-based Daughtercard for TIs C6000 family of DSKs 

    Gadhiok, Manik; Hardy, Ricky; Murphy, Patrick; Frantz, Patrick; Choi, Hyeokho; Cavallaro, Joseph R. (2005-06-01)
    In this paper we present an FPGA-based daughtercard designed for TIs C6000 family of DSP Starter Kits (DSKs). The hardware, initially designed for a course project, provides a platform for studying heterogeneous systems ...
  • Network and User Driven Alpha-Beta Onâ Off Source Model for Network Traffic 

    Sarvotham, Shriram; Riedi, Rudolf H.; Baraniuk, Richard G. (2005-06-01)
    We shed light on the effect of network resources and user behavior on network traffic through a physically motivated model. The classical onâ off model successfully captures the long-range, second-order correlations of ...
  • Multiscale Manifold Representation and Modeling 

    Choi, Hyeokho; Baraniuk, Richard G. (2005-03-01)
    Many real world data sets can be viewed as points in a higher-dimensional space that lie concentrated around a lower-dimensional manifold structure. We propose a new multiscale representation for such point clouds based ...
  • FFT-Accelerated Iterative MIMO Chip Equalizer Architecture For CDMA Downlink 

    Guo, Yuanbin; McCain, Dennis; Cavallaro, Joseph R. (2005-03-01)
    In this paper, we present a novel FFT-accelerated iterative Linear MMSE chip equalizer in the MIMO CDMA downlink receiver. The reversed form time-domain matrix multiplication in the Conjugate Gradient iteration is accelerated ...
  • High-Resolution Navigation on Non-Differentiable Image Manifolds 

    Wakin, Michael; Donoho, David; Choi, Hyeokho; Baraniuk, Richard G. (2005-03-01)
    The images generated by varying the underlying articulation parameters of an object (pose, attitude, light source position, and so on) can be viewed as points on a low-dimensional <i>image parameter articulation manifold</i> ...
  • A Multiscale Data Representation for Distributed Sensor Networks 

    Wagner, Raymond; Sarvotham, Shriram; Baraniuk, Richard G. (2005-03-01)
    Though several wavelet-based compression solutions for wireless sensor network measurements have been proposed, no such technique has yet appreciated the need to couple a wavelet transform tolerant of irregularly sampled ...
  • Optimal digital communication of analog signals 

    Memarzadeh, Mahsa; Johnson, Don (2005-03-01)
    In this paper, the problem of optimally communicating analog sources using a bandwidth and power limited digital system is considered. We propose and analyze optimal combined source-channel coding schemes that jointly ...
  • TCP-Africa: An Adaptive and Fair Rapid Increase Rule for Scalable TCP 

    King, Ryan; Baraniuk, Richard G.; Riedi, Rudolf H. (2005-03-01)
    High capacity data transfers over the Internet routinely fail to meet end-to-end performance expectations. The default transport control protocol for best effort data traffic is currently TCP, which does not scale well to ...
  • Analysis of noise reduction in redundant expansions under distributed processing requirements 

    Rozell, Chris; Johnson, Don (2005-03-01)
    We considered signal reconstruction with redundant expansions under distributed processing in noisy environments. Redundant expansions have the ability to reduce noise corrupting the coefficients, but distributed processing ...
  • Distributed Multiscale Data Analysis and Processing for Sensor Networks 

    Wagner, Raymond; Sarvotham, Shriram; Choi, Hyeokho; Baraniuk, Richard G. (2005-02-01)
    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, ...