A new statistical pattern recognition method has been developed for detection, recognition or measurement of patterns which are (much) smaller than the measure of the elementary pixel windows in the image screen. In t...
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A new statistical pattern recognition method has been developed for detection, recognition or measurement of patterns which are (much) smaller than the measure of the elementary pixel windows in the image screen. In this measurement the gray-level histogram of the objects examined is compared with the simulated histograms of different (in type or size) possible objects, and the recognition (of shape or measure) is taken on the basis of the comparison. This method does not need ultra-precise movement of the scanning sensors or any additional hardwares. Moreover, the examined pattern should be randomly distributed on the screen, or a random movement of camera (or target or both) is needed. Effect of noises are analyzed, and filtering processes are suggested in the histogram domain. Several examples of different shapes are presented through simulations and experiments.< >
This paper analyzes the robustness properties and modeling requirements for model-predictive control via Horizon Predictive control (HPC). The theory of Structured Singular Values is used to determine optimal values f...
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This paper analyzes the robustness properties and modeling requirements for model-predictive control via Horizon Predictive control (HPC). The theory of Structured Singular Values is used to determine optimal values for the correction horizon in HPC given user-provided uncertainty intervals and performance weights. Regarding system identification, control-relevant identification principles are used to provide guidelines for input signal design, prefiltered estimation, and uncertainty modeling. These results are tested experimentally using data from a methanol-isopropanol distillation column.
For pt.I, see ibid., p.1-10 (1992). The programmability (as a stored program) of the CNN universal machine is discussed. It is shown why and in which sense this machine is universal. The analogic type of algorithm is ...
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For pt.I, see ibid., p.1-10 (1992). The programmability (as a stored program) of the CNN universal machine is discussed. It is shown why and in which sense this machine is universal. The analogic type of algorithm is introduced. The application potential is reviewed and the biological relevance is analyzed. It is shown that the architecture is optimal not only for silicon implementations, but also for many biological information processing organs that have the same structure.< >
Various types of cellular neural networks (CNNs) are summarized, and a taxonomy of CNNs is given according to the different types of grids, processors, interactions, and modes of operation. The CNN universal machine i...
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Various types of cellular neural networks (CNNs) are summarized, and a taxonomy of CNNs is given according to the different types of grids, processors, interactions, and modes of operation. The CNN universal machine is introduced. The architecture and the key features of the CNN universal machine are outlined. An exhaustive list of references is given.< >
The authors show that the game of life algorithm, which is equivalent to a Turing machine, can be realized by cellular neural networks (CNNs). They also present a multipath CNN algorithm that demonstrates the capabili...
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The authors show that the game of life algorithm, which is equivalent to a Turing machine, can be realized by cellular neural networks (CNNs). They also present a multipath CNN algorithm that demonstrates the capabilities of analog/logic (analogic) software. Complex image processing tasks can be realized by programmable dual computing CNNs. A specific example of blob-counting in a gray-scale image is presented.< >
A method for the path-control of automated guided vehicles (AGVs) in computer integrated manufacturing (CIM) systems that combines the flexibility and easy installation of optical methods with the simplicity and robus...
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A method for the path-control of automated guided vehicles (AGVs) in computer integrated manufacturing (CIM) systems that combines the flexibility and easy installation of optical methods with the simplicity and robustness of the inductive method is proposed. Using a new computing paradigm, the cellular neural network (CNN), and a related device, the VLSI CNN chip, a very high speed solution that is less expensive than the conventional methods can be achieved. This AGV control complies with the requirements of CIM systems. Further advantages of the proposed system are as follows: fault tolerance and the ability to give instructions along the path, and the use of a simple local control.< >
We report on recent progress in the development of a computer-aided engineering (CAE) environment for nonlinear control system analysis and design based on sinusoidal-input describing function (SIDF) methods. Several ...
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We report on recent progress in the development of a computer-aided engineering (CAE) environment for nonlinear control system analysis and design based on sinusoidal-input describing function (SIDF) methods. Several major additions have been made to our nonlinear controls CAE software: ACSL macros were developed to allow the generation of SIDF models of nonlinear plants in a manner analogous to that of the SIMNON-based software developed earlier, and MATLAB routines were developed for the analysis of these models and for the design of general nonlinear controllers based on them. This software provides an integrated tool set for treating very general nonlinear systems with no restrictions on system order, number of nonlinearities, configuration, or nonlinearity type. Based on the new software presented here, the use of SIDF-based nonlinear control system analysis and design methods is substantially easier to carry out and more powerful than before
In an approach proposed by V.P. Kumar et al. (see Proc. IEEE Int. Conf. on computer-Aided Design, p.226-9, Nov. 1989) for the yield enhancement of programmable gate arrays (PGAs), an initial placement of a circuit is ...
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In an approach proposed by V.P. Kumar et al. (see Proc. IEEE Int. Conf. on computer-Aided Design, p.226-9, Nov. 1989) for the yield enhancement of programmable gate arrays (PGAs), an initial placement of a circuit is first obtained using a standard technique such as simulated annealing on a defect-free PGA. In the next step this placement is reconfigured so that the circuit is mapped onto the defect-free portion of a defective PGA chip with the same architecture. In the present work, the authors consider the problem of yield enhancement along the same lines as above not only for PGAs but also for wafer-scale-integrated arrays. A heuristic algorithm for reconfiguration based on a graph-theoretic formulation of the problem and a polynomial-time exact algorithm for a special case of the problem are presented. The reconfiguration algorithms are evaluated by comparing the routability and wire length of the reconfigured and initial placements of the circuit.< >
This article analyzes costs and relative benefits of several hundred flexible manufacturing systems (FMSs) in the world. The analyses are based on the computerized data bases, which make it easy to correlate different...
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We examine the tracking of 3-dimensional targets moving in a complex (e.g. highly textured) visual environment, which makes the application of methods relying on static segmentation and feature correspondence very pro...
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