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Abstract - DSP7

DSP7.1	A New Adaptive Notch Filter with Constrained Poles and Zeros Using Steiglitz-McBride Method M. Cheng, J. Tsai (National Chiao-Tung University, Taiwan, ROC) In this paper we present a new adaptive notch filter (ANF) using the well-known Steiglitz-McBride method (SMM) for an IIR filter with the constrained poles and zeros. The proposed ANF, termed as SMM-ANF, converges to the unbiased solution, has fast convergence speed, and requires less computational complexity than existing recursive maximum likelihood adaptive notch filters (RML-ANF) . In the stationary environments, we analyze SMM-ANF convergence properties using the ordinary differential equation (ODE) technique; we derive conditions for the SMM-ANF convergence solution unbiased. Simulations further display that SMM-ANF has better resolution in identifying frequencies of multiple sine waves than RML-ANF. In the nonstationary environments, we also show that SMM-ANF and RML-ANF have approximately identical tracking performance. Simulations are also done to verify the theoretically derived results.
DSP7.2	QRD-Based LSL Interpolators -- Part II: A QRD-Based LSL Interpolation Algorithm Y. Bai, J. Yuan (Fu Jen Catholic University, Taiwan, ROC) In this paper, we derive a QRD-LSL interpolation algorithm that can be used to construct order-recursive QRD-LSL interpolators based on the exact decoupling property developed in a companion paper. QRD-LSL predictors are well known and use past data samples to predict the present data sample while the QRD-LSL interpolators use both past and future data samples to estimate the present data sample. Except for an overall delay needed for physical realization, QRD-LSL interpolators may achieve much better performance than that of the QRD-LSL predictors.
DSP7.3	An Adaptive, High-Order, Notch Filter Using All-Pass Sections S. Torres, V. De Brunner (University of Oklahoma, USA) A fully adaptive infinite impulse response notch filter in cascade form is proposed to detect and track multiple time-varying frequencies in additive white noise. Based on transformations for digital filters in the frequency domain, the filter results in a minimal number of parameters. In addition, a simple adaptive algorithm with good tracking and convergence properties is obtained by using all-pass filters and truncating the gradient. Computer simulations are included to verify the competitive performance of this filter under a wide range of conditions. From this analysis, we conclude that our new design is computationally simple, achieves rapid convergence, and is consequently a good choice in many non-stationary environments.
DSP7.4	A Fast Instrumental Variable Affine Projection Algorithm K. Maouche, D. Slock (Institut Eurecom, France) We derive a new adaptive filtering algorithm called the Instrumental Variable Affine Projection (IVAP) algorithm and give its fast version (FIVAP algorithm). The IVAP algorithm departs from the AP algorithm and uses an IV. The IV process is generated in a way such that the new algorithm combines between the AP and the Fast Newton Transversal Filter (FNTF) algorithms. Simulations show that the IVAP algorithm is more robust to noise than the AP algorithm. With the IV, the sample covariance matrix loses its Hermitian property and its displacement structure is different from the one of the AP algorithm. Consequently, the derivation of a fast version is done by deriving the IV Sliding Window Covariance Fast Transversal Filter (IV SWC FTF) algorithm. Using this and other ingredients, we derive the FIVAP algorithm whose computational complexity is nearly the same as the one of the FAP algorithm.
DSP7.5	A New Definition of Continuous Fractional Hartley Transform S. Pei (National Taiwan University, Taiwan, ROC); C. Tseng (Hwa Hsia College, Taiwan, ROC); M. Yeh, J. Ding (National Taiwan University, Taiwan, ROC) This paper is concerned with the definition of the continuous fractional Hartley transform. First, a general theory of linear fractional transform is presented to provide a systematic procedure to define the fractional version of any well-known linear transforms. Then, the results of general theory are used to derive the definitions of fractional Fourier transform (FRFT) and fractional Hartley transform (FRHT) which satisfy the boundary conditions and additivity property simultaneously. Next, an important relationship between FRFT and FRHT is described. Finally, a numerical example is illustrated to demonstrate the transform results of delta function of FRHT.
DSP7.6	Distributed Adaptive Algorithms for Large Dimensional MIMO Systems B. Van Veen, O. Leblond, V. Mani, D. Sebald (University of Wisconsin, USA) A distributed algorithm for MIMO adaptive filtering is introduced. This algorithm distributes the adaptive computation over a set of linearly connected computational modules. Each module transmits data to and receives data from its nearest neighbor. A back-propagation LMS based algorithm is presented for adapting the parameters in each module. The performance surface is explored to identify upper bounds on each parameter and guidelines for choosing the LMS algorithm step sizes. An example illustrates application of the algorithm.
DSP7.7	Log Adaptive Filters - Structures and Analysis for the Scalar Case M. Rakijas, N. Bershad (University of California, Irvine, USA) Feed-forward multi-layer neural networks (MLNN's) are complex nonlinear learning systems which can be trained by well-known rules such as back-propagation (BP). The resulting adaptation procedures are extremely difficult to analyze for stochastic training data. Significant analytic results have been obtained for the single-layer case and for some simple two-layer cases. Recently, a structural simplification has been studied which models each threshold function as a linear device. This linearized MLNN can only create hyperplane decision rules after convergence. However, the multiplicative behavior of the layers may offer some performance advantages over linear adaptive algorithms (LMS or RLS) when used for a linear problem. A new log-domain linear MLNN adaptive structure is proposed and analyzed here. The log operation converts the layer multiplications into additions whereupon linear analysis techniques can be used. The transient and steady-state statistical behavior of the log linear MLNN is analyzed for Gaussian training data. Deterministic recursions are derived for the mean and fluctuation behavior of the new algorithm. These recursion are shown to be in excellent agreement with Monte Carlo simulations.
DSP7.8	A New QRD-Based Block Adaptive Algorithm M. Bhouri, M. Bonnet, M. Mboup (Universite Rene Descartes, France) In this paper we present a new robust adaptive algorithm. It is derived from the standard QR Decomposition based RLS (QRD-RLS) algorithm by introducing a non-orthogonal transform into the update recursion. Instead of updating an upper triangular matrix, as it is the case for the QRD-RLS, we adapt an upper triangular block diagonal matrix. The complexity of the algorithm, thus obtained, varies from O(N^2) to O(N) when the size of the diagonal blocks decreases. Simulations of the new algorithm have shown a better robustness than the standard QRD-based algorithm in the context of multichannel adaptive filtering with highly intercorrelated channels.
DSP7.9	Novel Cost Function Adaptation Algorithm for Echo Cancellation C. Cowan (Queen's University of Belfast, N. Ireland); C. Rusu (Tampere University of Technology, Finland) A new stochastic gradient algorithm for data echo cancellation, based on the cost function adaptation (CFA) is proposed. Qualities of the new adaptation algorithm as compared with that of the least mean square (LMS) and the least mean fourth (LMF) algorithms are demonstrated by means of simulations. Thus it is shown that continuous and automatic, adaptation of the error power yields a more satisfactory result. The cost function adaptation allows an increase in convergence rate and, at the same time, an improvement of residual error. The results were obtained with non-Gaussian binary sequences of data in presence of far-end signals in data echo-cancellers for full duplex digital data transmission over telephone lines.
DSP7.10	On the Performance of an Adaptation of Adichie's Rank Tests for Signal Detection: and its Relationship to the Matched Filter C. Brown, A. Zoubir, B. Boashash (Queensland University of Technology - Signal Processing Research Center, Australia) The Adichie rank test and signed rank test are adapted for signal detection. We establish a relationship with the correlation between a function of the signal to be detected and the ranks of the observed data. A comparison between the power of these tests and the constant false alarm rate matched filter (CFAR MF) shows that the rank tests perform better when longer observations are available and for the symmetric alpha stable distributions encountered in applications with impulsive interference.

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