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FUZZY-REASONING SUPPORTED BY PETRI NETS

IEEE TRANSACTIONS ON FUZZY SYSTEMS 1994年第2期2卷 135-150页

作者： BUGARIN, AJ BARRO, S Department of Electronics and Computation University of Santiago de Compostela Santiago de Compostela Spain

We develop a representational model for the knowledge base (KB) of fuzzy production systems with rule chaining based on the Petri net formalism. The model presents the execution of a KB following a data driven strategy based on the sup-min compositional rule of Inference. In this connection, algorithms characterizing different situations have been described, including the case where the KB is characterized by complete information about all the input variables and the case where it is characterized by ignorance of some of these variables. For this last situation we develop a process of ''incremental reasoning'';this process allows the KB to take information about previously unknown values into consideration as soon as such information becomes available. Furthermore, as compared to other solutions, the rule chaining mechanism we introduce is more flexible, and the description of the rules more generic. The computational complexity of these algorithms is O((C/2 + M + N)R(2)) for the ''complete information'' case and O((M + N)R(2)) and O(2(M + N)R(2)) for the other cases, where R is the number of fuzzy conditional statements of the KB, M and N the maximum number of antecedents and consequents in the rules and C the number of chaining transitions in the KB representation.

关键词： Fuzzy reasoning Petri nets Fuzzy control Fuzzy systems Fuzzy logic Production systems Process control algorithm design and analysis Input variables Control system synthesis

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THE KINEMATICS OF HYPER-REDUNDANT ROBOT LOCOMOTION

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IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION 1995年第6期11卷 781-793页

作者： CHIRIKJIAN, GS BURDICK, JW CALTECH DEPT MECH ENGNPASADENACA 91125

This paper considers the kinematics of hyper-redundant (or ''serpentine'') robot locomotion over uneven solid terrain, and presents algorithms to implement a variety of ''gaits.'' The analysis and algorithms are based on a continuous backbone curve model which captures the robot's macroscopic geometry. Two classes of gaits, based on stationary waves and traveling waves of mechanism deformation, are introduced for hyper-redundant robots of both constant and variable length, We also illustrate how the locomotion algorithms can be used to plan the manipulation of objects which are grasped in a tentacle-like manner. Several of these gaits and the manipulation algorithm have been implemented on a 30 degree-of-freedom hyper-redundant robot, Experimental results are presented to demonstrate and validate these concepts and our modeling assumptions.

关键词： Kinematics Mobile robots Spine Mechanical engineering algorithm design and analysis Solid modeling Computational geometry Morphology Humans Intestines

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A RECURSIVE TECHNIQUE FOR COMPUTING DELAYS IN SERIES-PARALLEL MOS-TRANSISTOR CIRCUITS

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IEEE TRANSACTIONS ON COMPUTER-AIDED design OF INTEGRATED CIRCUITS AND SYSTEMS 1991年第5期10卷 589-595页

作者： CAISSO, JP CERNY, E RUMIN, NC MCGILL UNIV DEPT ELECT ENGNVLSI DESIGN LABMONTREAL H3A 2A7QUEBECCANADA UNIV MONTREAL DEPT INFORMAT & RECH OPERATMONTREAL H3C 3J7QUEBECCANADA UNIV MONTREAL DEPT COMP SCI & OPERAT RESMONTREAL H3C 3J7QUEBECCANADA

An efficient recursive technique for computing the Elmore delay in series-parallel resistance-capacitance (RC) networks is presented. The time complexity of the algorithm is of the order of the number of resistors times the number of nodes to which the delay has to be computed. In this respect it is superior to other known methods, in particular that of Chan and Karplus. Although their algorithm is more general, the present method should be attractive, given the fact that many VLSI MOS circuits are based on design styles which are restricted to series-parallel transitor networks which, in particular, exclude bridges. A special type of series-parallel RC circuit occurs in interconnection networks driven by multiple sources. A variation on the first algorithm, which is especially useful in a hierarchical simulator, is presented for computing the Elmore delay in such networks.

关键词： Computer networks Resistors Delay effects Very large scale integration algorithm design and analysis MOSFETs Bridge circuits Multiprocessor interconnection networks Computational modeling Circuit simulation

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LEVINSON-TYPE EXTENSIONS FOR NON-TOEPLITZ SYSTEMS

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1991年第2期39卷 366-375页

作者： PORSANI, M ULRYCH, TJ PPPG Universidade Federal da Bahia Salvador Bahia Brazil Department of Geophysics and Astronomy University of British Columbia Vancouver BC Canada

We show that Levinson's basic principle for the solution of normal equations which are of Toeplitz form may be extended to the case where these equations do not possess this specific symmetry. The use of Levinson's principle allows us to obtain a compact (2 x 2) form to express a system of equations of arbitrary order. This compact form is the key expression in the development of recursive algorithms and allows a compact representation of the most important Levinson-type algorithms which are used in the analysis of seismic and time series data in general. In the case when the coefficient matrix does not possess any type of special structure, the number of multiplications and divisions required in the inversion is n3 - 2n2 + 4n. We illustrate the described method by application to various examples which we have chosen so that the coefficient matrix possess various symmetries. Specifically, we first consider the solution of the normal equations when the associated matrix is the doubly symmetric non-Toeplitz covariance matrix. Second, we obtain the solution of extended Yule-Walker equations where the coefficient matrix is Toeplitz but nonsymmetric. Finally, we briefly illustrate the approach by considering the determination of the prediction error operator when the NE are in fact of symmetric Toeplitz form.

关键词： Symmetric matrices Covariance matrix Equations algorithm design and analysis Deconvolution Entropy Spectral analysis Geophysics Astronomy

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LMS ADAPTATION WITH CORRELATED DATA - A SCALAR EXAMPLE

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1984年第4期32卷 695-700页

作者： BERSHAD, NJ LIAN, ZQ UNIV CALIF IRVINE DEPT RADIOL SCIIRVINECA 92717

In this note, the statistical behavior of the complex scalar LMS adaptation algorithm is investigated when the input data stream consists of statistically dependent inputs. The asymptotic time constant of the mean behavior of the algorithm is evaluated, taking into account the time correlation properties of the input data sequence. It is shown that the behavior of the correlated data case does not degrade significantly from the uncorrelated case until the input sequence is very highly correlated (ρ > 0.99).

关键词： Least squares approximation Covariance matrix Difference equations Adaptive filters Degradation Steady-state algorithm design and analysis Frequency domain analysis Error correction

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The transition matrix for linear circuits

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IEEE TRANSACTIONS ON COMPUTER-AIDED design OF INTEGRATED CIRCUITS AND SYSTEMS 1997年第5期16卷 427-436页

作者： Opal, A Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

The state transition matrix Phi (t) = e(At) plays an important role in the state variable analysis of linear time-invariant circuits. In this paper, we give a method to compute the equivalent matrix for a set of differential-algebraic equations, Specifically, the algorithm is illustrated for the modified nodal analysis (MNA). A benefit of using MNA formulation is that equation formulation is straightforward and computer-aided analysis of large circuits is simplified, Another benefit is that inconsistent initial conditions in the analysis of switched circuits is automatically and correctly handled by the algorithm, Comparison with the state variable approach is made, and application to the simulation of linear circuits is given, The method is based on circuit theory concepts accessible to all electrical engineers. In addition to the transition matrix, a numerical method to compute the zero state response of linear circuits for a restricted set of inputs is given, The transition matrix along with the zero state response results in a special algorithm that is used to compute the time response of lumped linear time-invariant circuits at equally spaced intervals of time, This method is compared with the solution of linear circuits by SPICE-like simulators.

关键词： Linear circuits algorithm design and analysis Computational modeling Circuit simulation Differential equations Computer aided analysis Circuit analysis Switched circuits Application software Circuit theory

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Modular neural networks for MAP classification of time series and the partition algorithm

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IEEE TRANSACTIONS ON NEURAL NETWORKS 1996年第1期7卷 73-86页

作者： Petridis, V Kehagias, A AMER COLL HIGHER STUDIES DEPT MATHGR-54006 PYLEAGREECE

We apply the partition algorithm to the problem of time-series classification, We assume that the source that generates the time series belongs to a finite set of candidate sources. Classification is based on the computation of posterior probabilities. Prediction error is used to adaptively update the posterior probability of each source. The algorithm is implemented by a hierarchical, modular, recurrent network. The bottom (partition) level of the network consists of neural modules, each one trained to predict the output of one candidate source. The top (decision) level consists of a decision module, which computes posterior probabilities and classifies the time series tb the source of maximum posterior probability. The classifier network is formed from the composition of the partition and decision levels. This method applies to deterministic as well. as probabilistic time series. Source switching can also be accommodated. We give some examples of application to problems of signal detection, phoneme, and enzyme classification. Zn conclusion, the algorithm presented here gives a systematic method for the design of modular classification networks. The method can be extended by various choices of the partition and decision components.

关键词： Neural networks Partitioning algorithms Error correction design methodology Speech Radar signal processing Signal detection Biochemistry algorithm design and analysis Pattern classification

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Greenput: A Power-Saving algorithm That Achieves Maximum Throughput in Wireless Networks

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IEEE-ACM TRANSACTIONS ON NETWORKING 2018年第2期26卷 906-919页

作者： Chang, Cheng-Shang Lee, Duan-Shin Su, Chia-Kai Natl Tsing Hua Univ Inst Commun Engn Hsinchu 300 Taiwan

The dynamic frame sizing algorithm is a throughput-optimal algorithm that can achieve maximum network throughput without the knowledge of arrival rates. Motivated by the need for energy-efficient communication in wireless networks, in this paper, we propose a new dynamic frame sizing algorithm, called the Greenput algorithm, that takes power allocation into account. In our Greenput algorithm, time is partitioned into frames, and the frame size of each frame is determined based on the backlogs presented at the beginning of a frame. To obtain a good delay-energy efficiency tradeoff, the key insight of our Greenput algorithm is to reduce transmit power to save energy when the backlogs are low so as not to incur too much packet delay. For this, we define a threshold parameter T-max (for the minimum time to empty the backlogs with maximum power allocation), and the Greenput algorithm enters the (mixed) power-saving mode when the backlogs are below the threshold. Using a large deviation bound, we prove that our Greenput algorithm is still throughput optimal. In addition to the stability result, we also perform a fluid approximation analysis for energy efficiency and average packet delay when T-max is very large. To show the delay-energy efficiency tradeoff, we conduct extensive computer simulations by using the Shannon formula as the channel model in a wireless network. Our simulation results show that both energy efficiency and average packet delay are quite close to their fluid approximations even when T-max is moderately large.

关键词： Queueing analysis optimization algorithm design and analysis

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MICROSTATISTIC LMS FILTERING

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1993年第3期41卷 1021-1034页

作者： CHEN, SP ARCE, GR UNIV DELAWARE DEPT ELECT ENGNNEWARKDE 19716

Signal decomposition has shown to be a useful tool for the design of robust and efficient estimators. Stack and microstatistic filters are among the filters that use the threshold decomposition architecture. The microstatistic filter, in particular, uses linear combinations on the set of decomposed (thresholded) signals to produce its estimate. Thus, stack and microstatistic filters can be regarded as Boolean and linear threshold filters, respectively. The design of the optimal microstatistic filter requires the statistical characterization of the decomposed signal set (microstatistics). In this paper, we develop adaptive microstatistic filters for applications where the second-order statistics of the thresholded signals are not known, or when they may be nonstationary. A multilevel threshold decomposition is used such that real valued stochastic processes can be filtered and such that the computation complexity of the algorithm can be arbitrarily specified by the designer. The adaptation uses the least mean squares error approach of the least mean square (LMS) algorithm. The convergence of the adaptive algorithm is proved. Due to the nonhomogeneous statistical characteristics of the thresholded signals, we can assign a different step-size adaptation parameter to each threshold level. We develop simple design guidelines for the set of nonhomogeneous step sizes which in practice yield better convergence characteristics.

关键词： Least squares approximation Convergence Filtering Adaptive filters Statistics Stochastic processes Computational complexity algorithm design and analysis Adaptive algorithm Guidelines

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analysis OF THE COMBINED EFFECTS OF FINITE SAMPLES AND MODEL ERRORS ON ARRAY-PROCESSING PERFORMANCE

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1994年第11期42卷 3073-3083页

作者： VIBERG, M SWINDLEHURST, AL BRIGHAM YOUNG UNIV DEPT ELECT & COMP ENGNPROVOUT 84602 STANFORD UNIV INFORMAT SYST LABSTANFORDCA 94305 ESL INC SUNNYVALECA

The principal sources of estimation error in sensor array signal processing applications are the finite sample effects of additive noise and imprecise models for the antenna array and spatial noise statistics. While the effects of these errors have been studied individually, their combined effect has not yet been rigorously analyzed. In this paper, we undertake such an analysis for the class of so-called subspace fitting algorithms. In addition to deriving;first-order asymptotic expressions for the estimation error, we show that an overall optimal weighting exists for a particular array and noise covariance error model. In a companion paper, the optimally weighted subspace fitting method is shown to be asymptotically equivalent with the more complicated maximum a posteriori estimator. Thus, for the model in question, no other method can yield more accurate estimates for large samples and small model errors. Numerical examples and computer simulations are included to-illustrate the obtained results and to verify the asymptotic analysis for realistic scenarios.

关键词： Sensor arrays Estimation error Antenna arrays Additive noise Computer errors Array signal processing Error analysis algorithm design and analysis Signal processing algorithms Maximum a posteriori estimation

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