Estimation of multipath channel response in frequency selectivechannels

A novel discrete-time method is proposed for estimating the impulse response of a frequency-selective digitally modulated communication channel. The received signal is first demodulated and sampled and then the fourth-order cumulants of the resulting discrete-time sequence are estimated. The method estimates the channel impulse response from the complex cepstrum of the aforementioned fourth-order cumulants (i.e. tricepstrum). The method depends only on the second- and fourth-order statistics of the transmitted sequence and is capable of reconstructing nonminimum-phase impulse responses. Monte Carlo simulation results demonstrate the effectiveness of the method, its low sensitivity to observation noise, and its improved performance in terms of probability of error or the reconstructed transmitted sequence     

Blind equalizers with simulated annealing optimization for digital communication systems

New batch-type methods and their recursive extensions are introduced for blind equalization of digital communication channels. Based on the underlying cost function of the existing Bussgang and cumulantfitting algorithms, simulated annealing (SA) optimization is successfully employed to identify and equalize the communication channels. Many of the existing blind equalization algorithms utilize a stochastic gradient approach to minimize non-linear cost functions. Owing to the multimodal nature of these functions, the gradient algorithms might converge to the wrong solution. In contrast, the proposed methods are based on a global optimization algorithm. the SA algorithm tends to avoid the local minima encountered. The feasibility and convergence behaviour of the proposed algorithms are examined by means of computer simulations. Computational complexity issues in the implementation of the algorithms are discussed.     

Spatially localized image-dependent watermarking for statistical invisibility and collusion resistance

We develop a novel video watermarking framework based on the collusion-resistant design rules formulated in a companion paper. We propose to employ a spatially-localized image dependent approach to create a watermark whose pairwise frame correlations approximate those of the host video. To characterize the spread of its spatially-localized energy distribution, the notion of a watermark footprint is introduced. Then we explain how a particular type of image dependent footprint structure, comprised of subframes centered around a set of visually significant anchor points, can lead to two advantageous results: pairwise watermark frame correlations that more closely match those of the host video for statistical invisibility, and the ability to apply image watermarks directly to a frame sequence without sacrificing collusion-resistance. In the ensuing overview of the proposed video watermark, two new ideas are put forward: synchronizing the subframe locations using visual content rather than structural markers and exploiting the inherent spatial diversity of the subframe-based watermark to improve detector performance. Simulation results are presented to show that the proposed scheme provides improved resistance to linear frame collusion, while still being embedded and extracted using relatively low complexity frame-based algorithms.     

Nonminimum phase channel deconvolution using the complex cepstrumof the cyclic autocorrelation

New discrete time blind deconvolution methods are proposed for nonminimum phase linear channels driven by cyclo-stationary inputs. The methods rely exclusively on second-order statistics and do not impose any constraints on the distribution of the channel input as in the case of methods based on higher-order statistics. The output of the channel is fractionally sampled and then the complex cepstrum of the cyclic autocorrelation is obtained. It is shown that this complex cepstrum preserves nonminimum phase information and thus the identification of nonminimum phase channels is possible. Practical constraints in the implementation of the methods and channel identifiability conditions are discussed. The applicability of the methods to both channel identification and fractionally spaced linear and DFE equalization is described and verified by means of computer simulations     

Toward robust logo watermarking using multiresolution image fusion principles

This paper presents a novel robust watermarking approach called FuseMark based on the principles of image fusion for copy protection or robust tagging applications. We consider the problem of logo watermarking in still images and employ multiresolution data fusion principles for watermark embedding and extraction. A human visual system model based on contrast sensitivity is incorporated to hide a higher energy hidden logo in salient image components. Watermark extraction involves both characterization of attacks and logo estimation using a rake-like receiver. Statistical analysis demonstrates how our extraction approach can be used for watermark detection applications to decrease the problem of false negative detection without increasing the false positive detection rate. Simulation results verify theoretical observations and demonstrate the practical performance of FuseMark.     

Performance of wideband,non-linearly amplified PAM cable systems

The performance of wide-band non-linearly amplified, i.e. power efficient, 2-, 4-, 8-, 16- and 32-level PAM digital cable systems is studied. The effect of amplitude and phase non-linearities (AM to AM) and (AM to PM) on the error rate performance and on the received eye diagrams is analysed by computer simulations and experimentally. We demonstrate that significant performance improvement could be attained by means of predistortion linearization, prior to the transmit (high power) amplifier, and by simple modification of the threshold decoding levels in the receiver.     

Blind equalization using a tricepstrum-based algorithm

An adaptive blind equalization method is introduced for nonminimum phase communication channels. The method estimates the inverse channel impulse response, by using the complex cepstrum of the fourth-order cumulants (tricepstrum) of the synchronously sampled received signal. As such, the proposed adaptive method depends only on the statistics of the received sequence, and is capable of reconstructing separately both the minimum and maximum phase response of the channel. It is demonstrated, by means of extensive simulations, that the proposed tricepstrum-based equalization scheme performs well and outperforms other existing blind equalizers, at the expense of higher computational complexity     

A novel blind deconvolution scheme for image restoration usingrecursive filtering

We present a novel blind deconvolution technique for the restoration of linearly degraded images without explicit knowledge of either the original image or the point spread function. The technique applies to situations in which the scene consists of a finite support object against a uniformly black, grey, or white background. This occurs in certain types of astronomical imaging, medical imaging, and one-dimensional (1-D) gamma ray spectra processing, among others. The only information required are the nonnegativity of the true image and the support size of the original object. The restoration procedure involves recursive filtering of the blurred image to minimize a convex cost function. We prove convexity of the cost function, establish sufficient conditions to guarantee a unique solution, and examine the performance of the technique in the presence of noise. The new approach is experimentally shown to be more reliable and to have faster convergence than existing nonparametric finite support blind deconvolution methods. For situations in which the exact object support is unknown, we propose a novel support-finding algorithm