By Topic

Signal Processing Letters, IEEE

Issue 7 • Date July 2003

Filter Results

Displaying Results 1 - 8 of 8
  • On the design and efficient implementation of the Farrow structure

    Page(s): 189 - 192
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (367 KB) |  | HTML iconHTML  

    This article proposes an efficient implementation of the Farrow (1988) structure using sum-of-powers-of-two (SOPOT) coefficients and multiplier-block (MB). In particular, a novel algorithm for designing the Farrow coefficients in SOPOT form is detailed. Using the SOPOT coefficient representation, coefficient multiplication can be implemented with limited number of shifts and additions. Using MB, the redundancy between multipliers can be fully exploited through the reuse of the intermediate results generated. Design examples show that the proposed method can greatly reduce the complexity of the Farrow structure while providing comparable phase and amplitude responses. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • New results of phase shifting in the wavelet space

    Page(s): 193 - 195
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (265 KB) |  | HTML iconHTML  

    This paper investigates the relationship between even-phase coefficients and odd-phase coefficients in a two-channel perfect reconstruction filter bank. We demonstrate that they are linked to each other by a unique phase-shifting matrix. In the case of multilevel wavelet decomposition, we present an efficient recursive solution to directly perform phase shifting in the wavelet space. Our proposed solution can also be easily generalized into the case of two-dimensional wavelet transform. Direct phase-shifting methods in the wavelet space have potential applications in wavelet-based image/video coding and compressed domain processing. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Nonlinear multiclass discriminant analysis

    Page(s): 196 - 199
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (339 KB) |  | HTML iconHTML  

    An alternative nonlinear multiclass discriminant algorithm is presented. This algorithm is based on the use of kernel functions and is designed to optimize a general linear discriminant analysis criterion based on scatter matrices. By reformulating these matrices in a specific form, a straightforward derivation allows the kernel function to be introduced in a simple and direct way. Moreover, we propose a method to determine the value of the regularization parameter /spl tau/, based on this derivation. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A performance analysis of multipath direction finding with temporal smoothing

    Page(s): 200 - 203
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (349 KB) |  | HTML iconHTML  

    Subspace-based direction finding techniques, such as MUSIC, encounter great difficulty when the received signals on the antenna array are coherent. This problem can be solved by conventional spatial smoothing methods, which require at least 3M/2 antennas to resolve M coherent signals. A previously proposed preprocessing approach called temporal smoothing requires only M+1 antennas given M coherent signals. In this letter, a block-sampling temporal smoothing scheme is introduced, and we derive the MSE in the bearing estimation with temporal smoothing. Finally, the performance of the temporal smoothing is compared with the spatial smoothing. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Speech probability distribution

    Page(s): 204 - 207
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (453 KB) |  | HTML iconHTML  

    It is demonstrated that the distribution of speech samples is well described by Laplacian distribution (LD). The widely known speech distributions, i.e., LD, Gaussian distribution (GD), generalized GD, and gamma distribution, are tested as four hypotheses, and it is proved that speech samples during voice activity intervals are Laplacian random variables. A decorrelation transformation is then applied to speech samples to approximate their multivariate distribution. To do this, speech is decomposed using an adaptive Karhunen-Loeve transform or a discrete cosine transform. Then, the distributions of speech components in decorrelated domains are investigated. Experimental evaluations prove that the statistics of speech signals are like a multivariate LD. All marginal distributions of speech are accurately described by LD in decorrelated domains. While the energies of speech components are time-varying, their distribution shape remains Laplacian. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Coherent integration loss due to white Gaussian phase noise

    Page(s): 208 - 210
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (252 KB) |  | HTML iconHTML  

    We develop a simple analytic expression for the change in coherent weighted integration gain due to a white Gaussian error or noise in the phase of the integrated samples. Our expression is shown by simulation to be very accurate for any reasonable value of phase noise standard deviation. The result is useful in estimating the performance impact on coherent signal processing systems of oscillator noise, residual motion compensation errors, and other system imperfections that are manifested primarily as phase errors. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multiwavelets denoising using neighboring coefficients

    Page(s): 211 - 214
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (484 KB) |  | HTML iconHTML  

    Multiwavelets give better results than single wavelets for signal denoising. We study multiwavelet thresholding by incorporating neighboring coefficients. Experimental results show that this approach is better than the conventional approach, which only uses the term-by-term multiwavelet denoising. Also, it outperforms neighbor single wavelet denoising for some standard test signals and real-life images. This is an extension to Cai and Silverman's (see Sankhya: Ind. J. Stat. B, pt.2, vol.63, p.127-148, 2001) work. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Copulas: a new insight into positive time-frequency distributions

    Page(s): 215 - 218
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (421 KB) |  | HTML iconHTML  

    We establish connections between Cohen-Posch (1985) theory of positive time-frequency distributions (TFDs) and copula theory. Both are aimed at designing joint probability distributions with fixed marginals, and we demonstrate that they are formally equivalent. Moreover, we show that copula theory leads to a noniterative method for constructing positive TFDs. Simulations show typical results. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Peter Willett
University of Connecticut
Storrs, CT 06269
peter.willett@uconn.edu