Showing papers in "Digital Signal Processing in 2011"

TL;DR: A Newton recursive and a Newton iterative identification algorithms are derived by using the Newton method (Newton-Raphson method) to reduce the sensitivity of the projection algorithm to noise, and to improve convergence rates of the SG algorithm.

TL;DR: A robust digital image watermarking scheme based on singular value decomposition (SVD) and a tiny genetic algorithm (Tiny-GA) and Experimental results demonstrate that the scheme is able to withstand a variety of image processing attacks.

TL;DR: A mechanism of block classification is used to compress the original image according to the DCT coefficients, in which blocks corresponding to different types are encoded to variable lengths, to provide improved restoration capability.

TL;DR: A novel approach is proposed which utilizes features of wavelet and curvelet transform, separately and adaptively, in 'homogeneous', 'non-homogeneous' and 'neither homogeneous nor non-Homogeneous' regions, which are identified by variance approach.

TL;DR: This paper presents an improved matrix multiplication method to solve the APSO problem, which is the fastest parallel algorithm compared to traditional PCNN, MOPCNN, and MPCNN methods.

TL;DR: A novel modification to the standard particle swarm optimization (PSO) technique is presented and the superiority of the proposed modified technique over other PSO-based techniques is illustrated, with an application to the important area of adaptive channel equalization.

TL;DR: The aim of investigation was to achieve and find values of the parameters which make Kalman filter useful in the real-time application of acceleration and angular rate signals filtering.

TL;DR: Experimental results show that the proposed audio watermarking approach maintains the high quality of the audio signal and that the watermark extraction and decryption are possible even in the presence of attacks.

TL;DR: An overview of an Illuminator Of Opportunity (IOO) passive radar research project being conducted at DSTO is presented, with a specific focus on the signal processing research directions that are being investigated.

TL;DR: Cross-validation testing results indicated that the accuracy, sensitivity, and specificify of EMD-SVD features extracted are all remarkable higher than that of DWT- SVD method, thus, practical guiding significance for diagnosing tremor types in clinic is provided.

TL;DR: Simulation results, based on the tracking of an object falling in space, are presented, which substantiate practical validity of the superior performance of a fore-active tracking radar over a traditional active radar with fixed waveform.

TL;DR: A new FIR adaptive filtering algorithm based on the Quasi-Newton (QN) optimization algorithm that uses a variable step-size in the coefficient update equation that leads to an improved performance.

TL;DR: This paper analyzes the improved performance of the proposed character segmentation algorithm in comparison to others presented in the literature from accuracy and computational complexity points of view and concludes that proposed approach enhances the cursive script segmentation accuracy with minimum computational complexity.

TL;DR: The results show that during meditation the width of Poincare plot tended to increase as the lag increased, and its' adaptation to the chaotic nature of the biological signals could be useful to evaluate heart rate signals during meditation.

TL;DR: It is found from the test results that the 3-D Cohen-Daubechies-Feauveau 9/7 symmetric wavelet along with the3-D SPIHT encoder yields the best compression result.

TL;DR: A new online signature verification system based on Mellin transform in combination with an MFCC is presented and Experimental result indicates that the combination proposed method with neural network have better performance.

TL;DR: The problem of estimating the frequency of a complex single tone is considered and two iterative Fourier interpolation algorithms are generalized by introducing an additional parameter to allow for selection of the Fouriers interpolation coefficients relative to the true frequency.

TL;DR: This paper presents a solution for user-independent recognition of isolated Arabic sign language gestures by encapsulating the movements of the segmented hands in a bounding box and transforming the frequency domain using Discrete Cosine Transformation (DCT).

TL;DR: A novel digital watermarking approach for copyright protection and authentication of medical images based on the wavelet transformation that is invisible to human eyes, robust against a wide variety of common attacks and reliable enough for tracing colluders is identified.

TL;DR: Using the prototypes and partition matrix obtained by fuzzy c-means clustering algorithm, a fuzzy similarity measure for spectral clustering (FSSC) is developed and the K-nearest neighbor sparse strategy is introduced into FSSC and applied to texture image segmentation.

TL;DR: Results using public available data show the capability of the method to successfully detect the DOA of several sources in real environments.

TL;DR: An LMI-based criterion for the global asymptotic stability of a class of uncertain discrete systems described by the Fornasini-Marchesini second local state-space (FMSLSS) model using generalized overflow nonlinearities is proposed.

TL;DR: This paper presents an online signature identification system based on global features that achieved 100% correct classification rate and a reduced set of nine features that were found to capture the essential characteristics required for signature identification.

TL;DR: A simpler framework to understand, use and generalize azimuthally symmetric convolution of signals defined on the 2-Sphere is demonstrated.

TL;DR: A novel adaptive decision feedback equalizer with the combination of finite impulse response filter and functional link neural network is introduced, which results in improving the convergence speed while retaining the lower steady-state error at the cost of a small increasing computational burden.

TL;DR: The behavior of two normalized forms of the Least-Mean Fourth (LMF) adaptive algorithm for Gaussian inputs is studied and the usefulness of the NLMF algorithm is open to question.

TL;DR: It is established that full channel state information for each self-selecting user can be obtained at the base station via a compressed-sensing technique with no increase in overhead for the uplink feedback channel.

TL;DR: A determinant criterion is proposed to constrain the solutions of non-negative matrix factorization problems and achieve unique and optimal solutions in a general setting, provided an exact solution exists.

TL;DR: A new adaptive equalization technique is proposed that combines both the least-mean-fourth (LMF) algorithm, which is governed by a non- Mean-square cost function, with a power-of-two quantizer (PTQ) in the coefficient update process, which greatly reduces the computational cost involved and which therefore makes the proposed technique applicable to time-varying environments.

TL;DR: A new hyperbolic distribution andhyperbolic mask for edge detection is introduced and edge-detection error probability as a function of the half mask size m is estimated using both masks in Gaussian- andHyperbolic-distributed pixel-intensity images.