作者：
G. GovindP.A. RamamoorthyM. L. 30
Signal Processing and Computer Vision Group Department of Electrical and Computer Engineering University of Cincinnati Cincinnati OH USA
The similarities and differences between the conventional Volterra series techniques and the neural network approach are discussed. The analysis is done from the point of view of representation capabilities for nonlin...
The similarities and differences between the conventional Volterra series techniques and the neural network approach are discussed. The analysis is done from the point of view of representation capabilities for nonlinear systems, and it is shown that a small neural network can represent high-order nonlinear systems, whereas a very large number of terms are required for an equivalent Volterra series representation. This is shown by means of a series expansion of a neural network. Issues common to the two nonlinear modeling approaches are analyzed
The statistical properties of discrete morphological filters are analyzed by utilizing the connection between morphological and stack filters. Analytical expressions of the output distribution of basic morphological f...
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The statistical properties of discrete morphological filters are analyzed by utilizing the connection between morphological and stack filters. Analytical expressions of the output distribution of basic morphological filters are derived. For one-dimensional filters closed form expressions are given.< >
A distributed scheme for dynamic partitioning is investigated. Distributed procedures to split a subsystem and to combine subsystems are presented. The correctness of each of these two procedures is shown, and the com...
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A distributed scheme for dynamic partitioning is investigated. Distributed procedures to split a subsystem and to combine subsystems are presented. The correctness of each of these two procedures is shown, and the complexity is analyzed. The procedures are applicable to parallel computers that use interconnection networks, such as hypercube, omega, multistage cube, and extra-stage cube networks.< >
SIMD (single-instruction-stream, multiple-data-stream) architectures require mechanisms that efficiently enable and disable mask processors to support flexible programming. Most current SIMD architectures use local ma...
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SIMD (single-instruction-stream, multiple-data-stream) architectures require mechanisms that efficiently enable and disable mask processors to support flexible programming. Most current SIMD architectures use local masking. Global processor masks, specified by the control unit, are more efficient for tasks where the masking is data independent. An efficient hybrid masking technique that supports global masking, as well as local masking, for SIMD architectures constructed from standard microprocessors is proposed. A design for the hybrid mechanism is described, and its experimental performance using the existing PASM prototype is examined. It is shown that the hybrid masking technique can increase the utilization of PEs and thus increase performance, the degree of improvement being algorithm dependent.< >
The planning problem is considered for a mobile manipulator system which must perform a sequence of tasks defined by position, orientation, force, and moment vectors at the end effector. Each task can be performed in ...
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The planning problem is considered for a mobile manipulator system which must perform a sequence of tasks defined by position, orientation, force, and moment vectors at the end effector. Each task can be performed in multiple configurations due to the redundancy introduced by mobility. The planning problem is formulated as an optimization problem in which the decision variables for mobility (base position) are separated from the manipulator joint angles in the cost function. The resulting numerical problem is nonlinear with nonconvex, unconnected feasible regions in the decision space. Simulated annealing is proposed as a general solution method for obtaining near-optimal results. The problem formulation and numerical solution by simulated annealing are illustrated for a positioning system with five degrees of freedom. These results are compared with results obtained by conventional nonlinear programming techniques customized for the particular example system.< >
An approach to online fault detection and diagnosis in automated manufacturing systems with discrete controls and sensing is described. The approach is based on the concept of behavioural models of the individual syst...
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An approach to online fault detection and diagnosis in automated manufacturing systems with discrete controls and sensing is described. The approach is based on the concept of behavioural models of the individual system components. These models, which can be developed while the system is being designed, characterize the responses of the devices in the system to arbitrary input signals over the range of acceptable operating conditions. The expected flow of signals through the system, from control inputs to sensor outputs, is captured in the behavioural model dynamics. This model provides the basis for online fault detection by generating expected system response signals which are compared online, in real-time, to the actual sensor signals from the system. Fault diagnosis is accomplished by maintaining a current set of operational assumptions which identify the system components which could cause deviations from the expected behavior.< >
Three knowledge-based texture image segmentation systems are described, and their performance on a real test image is analyzed. The image is a small piece of a seismic section and the objective is to segment it into z...
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Three knowledge-based texture image segmentation systems are described, and their performance on a real test image is analyzed. The image is a small piece of a seismic section and the objective is to segment it into zones of common signal texture. The first system is based on a run length statistics algorithm extended by a decision process which incorporates heuristic rules to influence the segmentation. The second and third systems are based on texture energy measurement algorithms augmented by two different knowledge-based classification processes. The knowledge-based process of the second system is controlled by a parallel region growing scheme, and that of the third system is controlled by an iterative quadtree-splitting scheme. The results show that the third system, texture-energy measurement augmented by a knowledge-based quadtree-splitting process, provides a better segmentation of the test image than the other two.< >
作者：
J.R. DellerR.K. SniderControl
Systems and Signal Proceesing Research Group: Speech Processing Laboratory Department of Electrical Engineering Michigan State University East Lansing MI USA
A procedure for evaluating the likelihood of a hidden Markov model using only O(N/K) floating-point operations per observation is developed where N is the number of states in the model and K is a large integer. Experi...
A procedure for evaluating the likelihood of a hidden Markov model using only O(N/K) floating-point operations per observation is developed where N is the number of states in the model and K is a large integer. Experimental tests show that effective recognition of cerebral palsy speech requires highly connected models so that O(3N) to O(N/sup 2/) operations are necessary using conventional algorithms. The reduction in computational complexity is required for near-real-time recognition algorithms to be feasible on ordinary personal computers.< >
A knowledge-based texture image segmentation system is discussed in which knowledge is used at the segmentation level. The system is characterized by a control mechanism based on an iterative linked quadtree splitting...
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A knowledge-based texture image segmentation system is discussed in which knowledge is used at the segmentation level. The system is characterized by a control mechanism based on an iterative linked quadtree splitting scheme. The main advantages of this system include the possibility of incorporating knowledge from diverse sources and with different scales, and the classification process is balanced and less dependent on the order in which the image is processed. The performance of the system is illustrated on two test images from totally different applications. The first is a natural texture image of an outdoor scene, and the second is a seismic image of stacked seismic traces used in interpretation of the Earth's subsurface geology.< >
The authors describe a knowledge-based system for detecting the interior and exterior boundaries of the left ventricle (LV) from time-varying cross-sectional images of the beating heart obtained noninvasively by magne...
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The authors describe a knowledge-based system for detecting the interior and exterior boundaries of the left ventricle (LV) from time-varying cross-sectional images of the beating heart obtained noninvasively by magnetic resonance imaging (MRI). The system automatically classifies and measures cardiac function through estimates of LV wall thickness, wall motion, etc. The system is knowledge based and it makes use of Dempster-Shafer theory to manage the knowledge. This theory is also used to control the flow of system information for more efficient use of limited computational resources and memory space.< >
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