Showing papers in "Digital Signal Processing in 2006"

TL;DR: A selection procedure of mother wavelet basis functions applied for denoising of the ECG signal in wavelet domain while retaining the signal peaks close to their full amplitude is presented.

TL;DR: This work formulates the problem of sensor-scheduling for target tracking as a partially observable Markov decision process (POMDP), and develops a Monte Carlo solution method using a combination of particle filtering for belief-state estimation and sampling-based Q-value approximation for lookahead.

TL;DR: The performance of the proposed CIC roll-off compensation filter is confirmed through computer simulation in such a way that bit error rate (BER) is minimized by compensating the roll- off characteristics.

TL;DR: The results demonstrate the usefulness of the proposed scheme for the incorporation of additional speed information and illustrate the opportunity of the particle filtering and mixture Kalman filtering to incorporate constraints in a natural way, providing reliable tracking and correct classification.

TL;DR: The proposed method is based on a hybrid method that uses feature selection and artificial immune recognition system (AIRS) with fuzzy resource allocation mechanism and it was very promising with regard to the other classification applications in literature for this problem.

TL;DR: An algorithm based on the cubic phase function, which is efficient to estimate the parameters of monocomponent first-, second-, and third-order polynomial phase signal, is presented to remove the identifiability problem of multicomponent chirp signals.

TL;DR: A new FOC-ESPRIT method of2-D direction finding based on the fractional order correlation and subspace technique for underwater 2-D source localization using a vector hydrophones array under alpha-stable noise conditions is proposed.

TL;DR: A number of IS data approaches that parallel the methods most commonly used for spectral analysis of RS data: the periodogram (PER), the Capon method (CAP), the multiple-signal characterization method (MUSIC), and the estimation of signal parameters via rotational invariance technique (ESPRIT).

TL;DR: This work addresses the problem of detecting the presence of hidden messages in audio by developing a detector based on the characteristics of the denoised residuals of the audio file, which may consist of a mixture of speech and music data.

TL;DR: A method for classifying a ship based on 3D scatterer information from a sequence of 2DISAR images is described and a preliminary classification result for simulated ISAR images of nine types of ship is provided.

TL;DR: This paper analyzes the CCF for the stationary processes of exponential auto-correlation function, with respect to two important types of sensor sampling kernels, and demonstrates that the Gaussian function is a better and more robust approximation of CCF than the parabola.

TL;DR: This technique uses MP method to compute the DOA of the signals using a very efficient computational procedure in which the complexity of the computation can be reduced significantly by using a unitary matrix transformation.

TL;DR: It is shown that this problem of adaptive beam scheduling to minimise target tracking error with a phased array radar can be posed in a framework that is similar to a particular type of dynamic programming problem known as the restless bandit problem.

TL;DR: A new algorithm has been developed to minimize the objective function by optimizing the filter tap weights by using Marquardt optimization method, which is better than that of the already existing methods.

TL;DR: This paper presents a novel method for differential diagnosis of erythemato-squamous disease based on fuzzy weighted pre-processing, k-NN (nearest neighbor) based weightedPre- processing, and decision tree classifier, which has reached to 86.18, 97.57, and 99.00% classification accuracies using 20-fold cross validation.

TL;DR: An intelligent methodology for diagnosing incipient faults in rotating machinery using wavelet neural network techniques in combination with a new evolutionary learning algorithm based on a hybrid of the constriction factor approach for particle swarm optimization technique and the gradient descent technique is presented.

TL;DR: It is shown that in many cases of interest DPD should be selected as the preferred method of localization in the presence of model errors caused by multipath, calibration errors, mutual coupling, etc.

TL;DR: A computationally simple iterative blind image deconvolution method which is based on non-linear adaptive filtering and is applicable to minimum as well as mixed phase blurs.

TL;DR: In this paper, a wavelet transform called Spikelet was designed and optimized to spike and overlap pattern recognition in the digitalized signal that comes from H1, a motion-sensitive neuron of the fly's visual system.

TL;DR: D diagnosis of thyroid disease was conducted using principles component analysis, k-nearest neighbor based weighted pre-processing and adaptive neuro-fuzzy inference system (ANFIS), which was very promising with regard to the other classification applications in literature for this problem.

TL;DR: Chan's circular functional model is used to describe the distribution of points and it is found that the bias approaches zero as the noise variance diminishes and that the variance approaches the Cramer–Rao lower bound.

TL;DR: This paper presents an extension of the matrix pencil method to simultaneously estimate the DOA along with the operating frequency of each of the signals and illustrates how to carry out the broadband DOA estimation procedure using realistic antenna elements located in a conformal array.

TL;DR: A wavelet based set partitioning in hierarchical trees (SPIHT) coder for progressive transmission of DICOM images proves that it provides diagnostically useful information as rapidly as possible utilizing minimum bandwidth than variants of JPEG as reported in literature.

TL;DR: A completely automatic and numerically reliable algorithm is developed that estimates the spectrum and the autocorrelation function in randomly missing data problems that was better than what can be obtained with other methods, including the famous expectation-maximization (EM) algorithm.

TL;DR: This study proposes a linear algebra formulation which exploits the definition of congruent matrix pencils and shows that the solution and its constraints are independent of the way the matrix pencil is computed.

TL;DR: This paper takes a reinforcement learning approach to adaptively schedule a multi-modality sensor so as to most quickly and effectively detect the presence of smart targets and track them as they travel through a surveillance region.

TL;DR: A variant of the set partitioned embedded block coder (SPECK) image compression called listless SPECK (LSK) is presented, which operates without lists and is suitable for a fast, simple hardware implementation.

TL;DR: A new method is proposed for determining the ARMA model parameters from the coefficients of a finite-order EMA model via simple computations using the estimated EMA and AR parameters.

TL;DR: This paper reformulates the diagonalisation problem as a convex optimisation problem on a Riemannian manifold and is thus able to guarantee global convergence to the optimal diagonaliser.

TL;DR: A simple and efficient design of prototype filters for cosine-modulated filterbanks is proposed, resulting in near perfect reconstruction (NPR) filterbanks, however, higher filter order is required to get NPR solution.