Information Theory and Reliable Communication

Array processing involves manipulation of signals induced on various antenna elements. Its capabilities of steering nulls to reduce cochannel interferences and pointing independent beams toward various mobiles, as well as its ability to provide estimates of directions of radiating sources, make it attractive to a mobile communications system designer. Array processing is expected to play an important role in fulfilling the increased demands of various mobile communications services. Part I of this paper showed how an array could be utilized in different configurations to improve the performance of mobile communications systems, with references to various studies where feasibility of apt array system for mobile communications is considered. This paper provides a comprehensive and detailed treatment of different beam-forming schemes, adaptive algorithms to adjust the required weighting on antennas, direction-of-arrival estimation methods-including their performance comparison-and effects of errors on the performance of an array system, as well as schemes to alleviate them. This paper brings together almost all aspects of array signal processing.

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Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations

Sphere Packings, Lattices and Groups

Tremor was suppressed by test stimulation of the thalamic ventralis intermedius (VIM) nucleus at high frequency (130 Hz) during stereotaxy in nonanesthetized patients suffering from Parkinson's disease or essential tremor. Ventralis intermedius stimulation has since been used by the authors over the last 8 years as a treatment in 117 patients with movement disorders (80 cases of Parkinson's disease, 20 cases of essential tremor, and 17 cases of various dyskinesias and dystonias including four multiple sclerosis). Chronic electrodes were stereotactically implanted in the VIM and connected to a programmable stimulator. Results depend on the indication. In Parkinson's disease patients, tremor, but not bradykinesia and rigidity, was selectively suppressed for as long as 8 years. Administration of L-Dopa was decreased by more than 30% in 40 Parkinson's disease patients. In essential tremor patients, results were satisfactory but deteriorated with time in 18.5% of cases, mainly for patients who presented an action component of their but deteriorated with time in 18.5% of cases, mainly for patients who presented an action component of their tremor. In other types of dyskinesias (except multiple sclerosis), results were much less favorable. Fifty-nine patients underwent bilateral implantation and 14 other patients received implantation contralateral to a previous thalamotomy. Thirty-seven patients (31.6%) experienced minor side effects, which were always well tolerated and immediately reversible. Three secondary scalp infections led to temporary removal of the implanted material. There was no permanent morbidity. This tremor suppression effect could be due to the inhibition or jamming of a retroactive loop. Chronic VIM stimulation, which is reversible, adaptable, and well tolerated even by patients undergoing bilateral surgery (74 of 117 patients) and by elderly patients, should replace thalamotomy in the regular surgical treatment of parkinsonian and essential tremors.

Chronic electrical stimulation of the ventralis intermedius nucleus of the thalamus as a treatment of movement disorders

The paper describes the method of determining direction and frequency content of the brain activity flow. The method was formulated in the framework of the AR model. The transfer function matrix was found for multichannel EEG process. Elements of this matrix, properly normalized, appeared to be good estimators of the propagation direction and spectral properties of the investigated signals. Simulation experiments have shown that the estimator proposed by us unequivocally reveals the direction of the signal flow and is able to distinguish between direct and indirect transfer of information. The method was applied to the signals recorded in the brain structures of the experimental animals and also to the human normal and epileptic EEG. The sensitivity of the method and its usefulness in the neurological and clinical applications was demonstrated.

A new method of the description of the information flow in the brain structures

In this work, we discuss a class of linear iterative learning control (ILC) systems which are iteration-varying with system output constraints. It can be shown that the objective of ensuring convergence of system output tracking error and satisfying system output constraints can be converted to a convex optimization problem, in which the objective function is quadratic and the constraints are convex. Under the proposed algorithm, tracking error convergence can be guaranteed over the iteration domain. A simulation study based on a wafer stage system is presented to demonstrate the efficacy of our approach.

Convex optimization based iterative learning control for iteration-varying systems under output constraints

In this work, we present a novel adaptive fault tolerant cooperative output tracking control scheme for a class of high-order nonlinear multiagent systems with a time-varying active leader, subject to constraints on the control input and agents' output. Each follower node has distinct nonlinear dynamics with both parametric and nonparametric uncertainties. Both multiplicative and additive actuator faults are considered. We show that under the proposed scheme, exponential convergence of the cooperative output tracking error into a small set around zero is guaranteed, while the constraint requirements on the system output will not be violated during operation, despite the presence of actuator faults and system uncertainties. State vectors of the agents and all other closed loop signals are shown to be bounded. An illustrative example is presented to further demonstrate the effectiveness of the proposed cooperative output tracking control scheme.

Adaptive cooperative output tracking control for input and output constrained multiagent systems with actuator faults

This paper studies the problem of achieving watermark semifragility in watermark-based authentication systems through a composite hypothesis testing approach. Embedding a semifragile watermark serves to distinguish legitimate distortions caused by signal-processing manipulations from illegitimate ones caused by malicious tampering. This leads us to consider authentication verification as a composite hypothesis testing problem with the watermark as side information. Based on the hypothesis testing model, we investigate effective embedding strategies to assist the watermark verifier to make correct decisions. Our results demonstrate that quantization-based watermarking is more appropriate than spread-spectrum-based methods to achieve the semifragility tradeoff between two error probabilities. This observation is confirmed by a case study of an additive Gaussian white noise channel with a Gaussian source using two figures of merit: 1) relative entropy of the two hypothesis distributions and 2) the receiver operating characteristic. Finally, we focus on common signal-processing distortions, such as JPEG compression and image filtering, and investigate the discrimination statistic and optimal decision regions to distinguish legitimate and illegitimate distortions. The results of this paper show that our approach provides insights for authentication watermarking and allows for better control of semifragility in specific applications.

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A Hypothesis Testing Approach to Semifragile Watermark-Based Authentication

This article introduces a technique for estimating samples of a random signal based on observations made by several observers and at different sampling rates. We consider a discrete-time mathematical model where an observer sees the original random signal x(n) through a bank of sensors which we model by linear filters and downsamplers. Each sensor, therefore, outputs a measurement signal v/sub i/(n) whose sampling rate is only a fraction of the sampling rate assumed for the original signal under observation. It is straightforward to show that the optimal least-mean-squares estimator for our problem is a linear operator F operating on v/sub i/(n)s. We observe, however, that to find F we need to know the power spectral density P/sub x/(e/sup jw/) of x(n) which is itself not observable. This motivates us to consider the possibility of estimating P/sub x/(e/sup jw/) using the observable low-rate data. We show that the statistical inference problem which addresses estimation of P/sub x/(e/sup jw/) given certain statistics of v/sub i/(n) is mathematically ill-posed. We resolve this ill-posed inference problem using the principle of maximum entropy. We show, moreover, that the proposed maximum entropy inference technique is a continuous mapping. Therefore, one might safely use it to estimate P/sub x/(e/sup jw/) based on approximate statistics of v/sub i/(n) obtained from the samples.

Multirate signal estimation

The decentralized robust servomechanism problem (DRSP) for colocated large flexible space structures (LFSS) under sensor and actuator failures is considered. A unified treatment of failures is enabled by introducing failure matrices. For colocated LFSS, stabilization, tracking of constant set points, and regulating against constant disturbances such that no “spillover effects” occur, can be simultaneously handled using a fault-accommodating decentralized tuning PID error-feedback controller. Necessary and sufficient conditions for solvability of the DRSP for colocated LFSS under sensor and actuator failures are derived in our analysis. In the case when each control agent is single-input/single-output, the decentralized fault-tolerant controller becomes particularly simple to implement. Steady-state output matrices for failed outputs are computed, and are found to be independent of controller gains.

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Raymond H. Kwong

Papers

Convex optimization based iterative learning control for iteration-varying systems under output constraints

Adaptive cooperative output tracking control for input and output constrained multiagent systems with actuator faults

A Hypothesis Testing Approach to Semifragile Watermark-Based Authentication

Multirate signal estimation

Decentralized robust servomechanism problem for large flexible space structures under sensor and actuator failures