Now showing items 398-417 of 508

  • SCAN - Speech Content Based Audio Navigator: A Systems Overview 

    Choi, John; Hindle, Don; Hirschberg, Julia; Magrin-Chagnolleau, Ivan; Nakatani, Christine; Pereira, Fernando; Singhal, Amit; Whittaker, Steve (1998-01-15)
    SCAN (Speech Content based Audio Navigator) is a spoken document retrieval system integrating speaker-independent, large-vocabulary speech recognition with information-retrieval to support query-based retrieval of information ...
  • Second-Order Statistical Measures for Text-Independent Speaker Identification 

    Bimbot, Frederic; Magrin-Chagnolleau, Ivan (1995-08-20)
    This article presents an overview of several measures for speaker recognition. These measures relate to second-order statistical tests, and can be expressed under a common formalism. Alternate formulations of these measures ...
  • Sharing Knowledge and Building Communities in Signal Processing 

    Baraniuk, Richard G.; Burrus, C. Sidney; Johnson, Don; Jones, Douglas L. (2004-09-01)
    The textbook has traditionally been the fundamental tool of university teaching. The text both serves as the repository of facts and information and provides the recommended structure and sequence for teaching and learning ...
  • Shear Madness: New Orthonormal Bases and Frames Using Chirp Functions 

    Baraniuk, Richard G.; Jones, Douglas L. (1993-12-01)
    The proportional-bandwidth and constant-bandwidth time-frequency signal decompositions of the wavelet, Gabor, and Wilson orthonormal bases have attracted substantial interest for representing nonstationary signals. However, ...
  • Shift-Invariant Denoising using Wavelet-Domain Hidden Markov Trees 

    Romberg, Justin; Choi, Hyeokho; Baraniuk, Richard G. (1999-10-20)
    Wavelet-domain hidden Markov models have proven to be useful tools for statistical signal and image processing. The hidden Markov tree (HMT) model captures the key features of the joint statistics of the wavelet coefficients ...
  • Shift-Invariant Denoising using Wavelet-Domain Hidden Markov Trees 

    Romberg, Justin; Choi, Hyeokho; Baraniuk, Richard G. (1999-10-01)
    Wavelet-domain hidden Markov models have proven to be useful tools for statistical signal and image processing. The hidden Markov tree (HMT) model captures the key features of the joint statistics of the wavelet coefficients ...
  • Signal and Information Processing for Wireless Communication Systems 

    Bhashyam, Srikrishna (2001-04-20)
    Next generation wireless communication systems need to support access to multimedia data available on the internet. This universal wireless access to multimedia data requires data rates and quality of service that are ...
  • A Signal Dependent Time Frequency Representation: Optimal Kernel Design 

    Baraniuk, Richard G.; Jones, Douglas L. (1993-04-01)
    Time-frequency distributions (TFDs), which indicate the energy content of a signal as a function of both time and frequency, are powerful tools for time-varying signal analysis. The lack of a single distribution that is ...
  • Signal Estimation using Wavelet-Markov Models 

    Crouse, Matthew; Baraniuk, Richard G.; Nowak, Robert David (1997-04-01)
    Current wavelet-based statistical signal and image processing techniques such as shrinkage and filtering treat the wavelet coefficients as though they were statistically independent. This assumption is unrealistic; considering ...
  • The Signal Processing Information Base 

    Johnson, Don; Shami, P N (1993-10-20)
    The SPIB (Signal Processing Information Base) project at Rice University is discussed. This information base will provide the signal processing researcher and the applications engineer with data, programs, and papers that ...
  • SIGNAL PROCESSING TECHNIQUES BASED ON SPLINE FUNCTIONS 

    NETRAVALI, ARUN NARAYAN (1971)
  • Signal Transform Covariant to Scale Changes 

    Baraniuk, Richard G. (1993-09-01)
    A unitary signal transformation that is covariant by translation to scale changes (dilations and compressions) in the signal is formulated and justified. Unlike the Mellin transform, which is invariant to scale changes, ...
  • Signal-Dependent Time-Frequency Analysis using a Radially Gaussian Kernel 

    Baraniuk, Richard G.; Jones, Douglas L. (1993-01-15)
    Time-frequency distributions are two-dimensional functions that indicate the time-varying frequency content of one-dimensional signals. Each bilinear time-frequency distribution corresponds to a kernel function that ...
  • A Signal-Dependent Time-Frequency Representation: Fast Algorithm for Optimal Kernel Design 

    Baraniuk, Richard G.; Jones, Douglas L. (1994-01-01)
    A time-frequency representation based on an optimal, signal-dependent kernel has been proposed recetnly in an attempte to overcome one of the primary limitations of bilinear time-frequency distributions: that the best ...
  • A Simple Covariance Based Characterization of Joint Signal Representations of Arbitrary Variables 

    Jones, Douglas L.; Sayeed, Akbar M. (1996-01-20)
    Joint signal representations of arbitrary variables extend the scope of joint time-frequency representations, and provide a useful description for a wide variety of nonstationary signal characteristics. Cohen's marginal-based ...
  • 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 ...
  • A Simple Scheme for Adapting Time-Frequency Representations 

    Jones, Douglas L.; Baraniuk, Richard G. (1994-12-01)
    Signal-dependent time-frequency representations, by adapting their functional form to fit the signal being analyzed, offer many performance advantages over conventional representations. In this paper, we propose a simple, ...
  • A Simple Scheme for Adapting Time-Frequency Representations 

    Jones, Douglas L.; Baraniuk, Richard G. (1992-10-01)
    Current signal-dependent time-frequency representations are block-oriented methods suited only for short-duration signals. The authors propose a simple, computationally efficient technique for creating adaptive time-frequency ...
  • A Simple Statistical Analysis of Wavelet-based Multifractal Spectrum Estimation 

    Goncalves, Paulo; Riedi, Rudolf H.; Baraniuk, Richard G. (1998-11-01)
    The multifractal spectrum characterizes the scaling and singularity structures of signals and proves useful in numerous applications, from network traffic analysis to turbulence. Of great concern is the estimation of the ...