Institute for Systems Research
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Item A Practical Transmission System Based on the Human Visual Model for Satellite Channels(1999) Gu, Junfeng; Jiang, Yimin; Baras, John S.; Baras, John S.; ISR; CSHCNThis paper presents a practical architecture for joint source-channel coding of human visual model-based video transmission over a satellite channel. Perceptual distortion model just-noticeable-distortion (JND) is applied to improve the subjective quality of compressed videos. 3-D wavelet decomposition can remove spatial and temporal redundancy and provide the scalability of video quality.In order to conceal errors occurring under bad channel conditions, a novel slicing method and a joint source channel coding scenario that combines RCPC with CRC and utilizes the distortion information to allocate convolutional coding rates are proposed. A new performance index based on JND is proposed and used to evaluate the overall performance at different signal-to-noise ratios (SNR). Our system uses OQPSK modulation scheme.
The research and scientific content in this material has been submitted to Globecom'99. Item Closed-Loop Monitoring Systems for Detecting Incipient Instability(1998) Kim, Taihyun; Abed, Eyad H.; ISRMonitoring systems are proposed for the detection of incipientinstability in uncertain nonlinear systems. The work employsgeneric features associated with the response to noise inputsof systems bordering on instability. These features, called "noisy precursors" in the work of Wiesenfeld, also yield information onthe type of bifurcation that would be associated with thepredicted instability. The closed-loop monitoring systems proposedin the paper have several advantages over simple open-loop monitoring.The advantages include the ability to influence the frequencies atwhich the noisy precursors are observed, and the ability tosimultaneously monitor and control the system.Item Application of Auditory Representations on Speaker Identification(1997) Chi, Taishih; Shamma, S. A.; ISRThe noise-robustness of auditory spectrum and cortical representation is examined by applying it to text-independent speaker identification tasks. A Bayes classifier residing on an M-ary hypothesis test is employed to evaluate the robustness of the auditory cepstrum and demonstrate its superior performance to that of the well-studied mel-cepstrum. In addition, the phase feature of the wavelet-transform based multiscale cortical representation is shown to be much more stable than the magnitude feature in characterizing speakers by correlator technique, which is traditionally used in scene matching application. This observation is consistent with physiological and psychoacoustic phenomena. The underlying purpose of this study is to inspect the inherent robustness of auditory representations derived from a human perception-based model. The experimental results indicate that biologically motivated features significantly enhance speaker identification accuracy in noisy environments.Item Mathematical Programming Algorithms for Regression-based Nonlinear Filtering in IRN(1997) Sidiropoulos, N.D.; Bro, R.; ISRConstrained regression problems appear in the context of optimal nonlinear filtering, as well as in a variety of other contexts, e.g., chromatographic analysis in chemometrics and manufacturing, and spectral estimation. This paper presents novel mathematical programming algorithms for some important constrained regression problems in IRN . For brevity, we focus on four key problems, namely, locally monotonic regression (the optimal counterpart of iterated median filtering), and the related problem of piecewise monotonic regression, runlength-constrained regression (a useful segmentation and edge detection technique), and uni- and oligo- modal regression (of interest in chromatography and spectral estimation). The proposed algorithms are exact and efficient, and they also naturally suggest slightly suboptimal but very fast approximate algorithms, which may be preferable in practice.Item Zero-Crossing Rates of Some Non-Gaussian Processes with Application to Detection and Estimation(1996) Barnett, John T.; Kedem, B.; ISRIn this dissertation we present extensions of Rice's formula for the expected zero-crossing rate of a Gaussian process to some useful non-Gaussian cases. In particular, we extend Rice's formula to the class of stationary processes which are a monotone transformation of a Gaussian process, to countable mixtures of Gaussians, and to products of independent Gaussian processes. In all the above mentioned cases the expected zero-crossing rates are given for both continuous time and discrete time processes. We also investigate the application of parametric filtering, using zero-crossing count statistics, to the problem of frequency estimation in a mixed spectrum model and the application of mean- level-crossing counts of the envelope of a Gaussian process to a radar detection problem. For the radar problem we prove asymptotic normality of the level-crossings of the envelope of a Gaussian process and provide and expression for the asymptotic variance.Item Performance Analysis of Coherent TCM Systems with Diversity Reception in Slow Rayleigh Fading(1996) Al-Semari, Saud A.; Fuja, Tom E.; ISRCoherent trellis coded modulation (TCM) systems employing diversity combining are analyzed. Three different kinds of combining are considered: maximal ratio, equal gain, and selection combining. For each combining scheme, the cutoff rate parameter is derived assuming transmission over a fully- interleaved channel with flat, slow, Rayleigh fading; in addition, tight upper bounds on the pairwise error probabilities are derived. These upper bounds are expressed in product form to permit bounding of the BER via the transfer function approach. In each case it is assumed that the diversity branches are independent and that the channel state information (CSI) can be recovered perfectly.Also included is an analysis of maximal ratio combining when the diversity branches are correlated; the cutoff rate and a tight upper bound on the pairwise error probability are derived. It is shown that, with double diversity, a branch correlation coefficient as high as 0.5 results in only slight performance degradation.
Item Simultaneous Diversity Combining and Decoding for Fast Time- Varying Mobile Radio Channels(1996) Wang, H.; Liu, K.J. Ray; ISRIn slowly time-varying mobile radio channels, adaptive diversity combining can reduce multipath fading of desired signal and suppress interfering signals. However, for fast time-varying fading channels, there exist no effective techniques to achieve the same results. The continued use of decision directed adaptive array algorithms will cause error propagation. This paper presents a novel adaptive diversity combining technique with QRD- RLS based parallel weights tracking and a proposed M-D decoder. With moderate increase in complexity, this system significantly reduces error propagation in the decision directed array systems while maintaining the same tracking speed. Its effectiveness and much better performance then that of the conventional technique has been confirmed by computer simulation.Item Two-Dimensional Spatial Smoothing for Multipath Coherent Signal Identification and Separation(1995) Wang, H.; Liu, K.J. Ray; ISRThe existing spatial smoothing (SS) technique, although it is effective in decorrelating coherent signals, is considered applicable only to uniformly spaced linear arrays which are very sensitive to the directions-of-arrival (DOAs) and can be used to estimate azimuth angles only. To significantly improve the robustness of DOA estimation and of beamforming and to estimate both azimuth and elevation angles in a 3D multipath mobile radio environment, we developed techniques for applying SS to arrays of nonlinear geometry. We found and proved the necessary and sufficient conditions on an array configuration for applying SS. This array must have an orientational invariance structure with an ambiguity free center array, and the number of subarrays must be larger than or equal to the size of the largest group of coherent signals. We also studied the cause of ambiguities in a multipath environment. We found the necessary and sufficient conditions for a three-sensor array manifold to be ambiguity free and identified several higher order ambiguity situations. If an array is also central symmetric, the forward/backward spatial smoothing can be used to improve the resolution. Finally, we expanded the application of our technique not only to MUSIC and adaptive beamforming algorithms but also to ESPRIT algorithms. All the predicted results are verified by simulations.Item Quantization of Memoryless and Gauss-Markov Sources Over Binary Markov Channels(1994) Phamdo, N.; Alajaji, Fady; Farvardin, Nariman; ISRJoint source-channel coding for stationary memoryless and Gauss- Markov sources and binary Markov channels is considered. The channel is an additive-noise channel where the noise process is an M-th order Markov chain. Two joint source-channel coding schemes are considered. The first is a channel-optimized vector quantizer - optimized for both source and channel. The second scheme consists of a scalar quantizer and a maximum a posteriori detector. In this scheme, it is assumed that the scalar quantizer output has residual redundancy that can be exploited by the maximum a posteriori detector to combat the correlated channel noise. These two schemes are then compared against two schemes which use channel interleaving. Numerical results show that the proposed schemes outperform the interleaving schemes. For very noisy channels with high noise correlation, gains of 4 to 5 dB in signal-to-noise ratio are possible.Item Strong Converse, Feedback Channel Capacity and Hypothesis Testing(1994) Chen, Po-Ning; Alajaji, Fady; ISRIn light of recent results by Verdu ad Han on channel capacity, we examine three problems: the strong converse condition to the channel coding theorem, the capacity of arbitrary channels with feedback and the Neyman-Pearson hypothesis testing type-II error exponent. It is first remarked that the strong converse condition holds if and only is the sequence of normalized channel information densities converges in probability to a constant. Examples illustrating this condition are also provided. A general formula for the capacity of arbitrary channels with output feedback is then obtained. Finally, a general expression for the Neyman-Pearson type-II exponent based on arbitrary observations subject to a constant bound on the type-I error probability is derived.