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Analysis of Deficient-Length Partitioned-Block Frequency-Domain Adaptive Filters

IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2022年 30卷 456-467页

作者： Yang, Feiran Chinese Acad Sci Inst Acoust State Key Lab Acoust Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

This paper studies the convergence behavior of the partitioned-block frequency-domain adaptive filters (PBFDAF) for under-modeling scenarios. We focus on a family of the overlap-save PBFDAF algorithms with 50% overlap, including both of the constrained and unconstrained versions. The stochastic analysis of the constrained and unconstrained algorithms is carried out individually due to their convergence differences. For each algorithm, the frequency-domain error vector and the update equations are transformed into the time-domain counterparts, so we can analyze their convergence behavior completely in the time domain. We present the mean and mean-square convergence behavior of the augmented weight-error vector, and we obtain the closed-form expressions for the learning curve and the steady-state solutions. Based on the solution of the steady-state weight-error vector, we analyze if each version of the PBFDAF algorithm converges to the true solution and the Wiener solution. The theoretical model gains new insights into the convergence behavior of the deficient-length PBFDAF algorithms. The computer simulations support the theoretical model very well.

关键词： Time-domain analysis Convergence partitioning algorithms Frequency-domain analysis Speech processing Steady-state Computational modeling Adaptive filtering convergence behavior frequency-domain adaptive filter under-modeling

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Buffer-Assisted Network Updates in Timed SDN

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IEEE TRANSACTIONS ON COMMUNICATIONS 2021年第10期69卷 6822-6837页

作者： He, Xin Zheng, Jiaqi Dai, Haipeng Sun, Yuhu Dou, Wanchun Chen, Guihai Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Peoples R China

Although the logically-centralized perspective is offered in Software-Defined Networking (SDN), the data plane is still distributed. Update commands sent by the centralized controller are executed asynchronously and independently in each switch. The timed SDN enables synchronous and coordinated update operations as each update command can be triggered by a pre-defined timestamp. Prior work on timed update mainly focuses on producing a congestion-free update sequence, whereas finding a congestion-free timed update sequence may prolong the update time. Even worse, such an update order may not exist. In this paper, we propose Chronus(+), a novel timed update system that utilizes the switch buffer to shorten the update time while minimizing the switch buffer during updates. First, we formulate the Minimum Switch Buffer Problem (MSBP) as an integer linear programming and show its hardness. Then, we propose a set of efficient algorithms to solve the problem in polynomial time. Extensive evaluations in Mininet and large-scale simulations show that Chronus(+) can reduce the update time by at least 17% and the switch buffer size by at least 27% compared with state-of-the-art approaches.

关键词： Switches Control systems Propagation delay Protocols partitioning algorithms Network topology Transient analysis Timed SDN network updates switch buffer link congestion

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SINGLE-LAYER GLOBAL ROUTING

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 1994年第1期13卷 38-47页

作者： SARRAFZADEH, M LIAO, KF WONG, CK IBM CORP DIV TECHNOL PROD E FISHKILL FACIL HOPEWELL JCT NY 12533 USA IBM CORP DIV RES THOMAS J WATSON RES CTR YORKTOWN HTS NY 10598 USA

We introduce the single-layer global routing problem (SLGRP), also called homotopic routing or rubber-band- equivalent routing, and propose a technique for solving it. Given a set of nets, the proposed technique first determines the routing sequence based on the estimated congestion, the bounding-box length and priority. Then, it finds a routing path, being a sequence of tiles, for each net (one net at a time), avoiding ''congested'' areas. The overall goal of the algorithm is to maximize the number of routed nets. The proposed global router is the first true singlelayer global router ever reported in the literature. The size of tiles, omega x omega, is an input parameter in our algorithm. For omega = 1, the proposed global router serves as an effective detailed router. An optimal postprocessing algorithm, minimizing wire length and number of bends, under homotopic transformation, is presented. The technique has been implemented and tried out for randomly generated data. The algorithm is very efficient and produces good results.

关键词： Routing Very large scale integration Tiles Wire partitioning algorithms Large scale integration Integrated circuit interconnections Fabrication Clocks Wiring

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An Efficient Method to Accurately Cluster Large Number of High Dimensional Facial Images

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IEEE ACCESS 2023年 11卷 39934-39949页

作者： Kumar, K. B. Shibu Samuel, Philip Coll Engn Trivandrum Dept Comp Sci & Engn Thiruvananthapuram 695016 India Cochin Univ Sci & Technol Dept Comp Sci Kochi 682022 India

Accurately clustering large, high dimensional datasets is a challenging problem in unsupervised learning. K-means is considered to be a fast, widely used and accurate centroid based data partitioning algorithm for spherical datasets. However, its non-determinism and heavy dependence on the selection of initial cluster centers along with vulnerability to noise make it a poor candidate for clustering large datasets with high dimensionality. To overcome these, we develop a novel, nature inspired, centroid based clustering algorithm, inspired from the principles of particle physics. Our method ensures that the convergence to local optima and non-deterministic outputs are avoided. We experiment the method on large datasets of human face images. Besides, our method addresses the problem of outliers and presence of not well-separated data in these datasets. We use a deep learning model for extracting facial features into a vector of 128 dimensions. We validate the quality and accuracy of our methods using different statistical parameters like f-measure, accuracy, error rate, average in group proportion and normalized cluster size rand index. These evaluations show that our method exhibits better accuracy and quality in clustering large face image datasets, in comparison with other existing mechanisms. The strength of our algorithms is more visible as the size of the dataset grows.

关键词： Face recognition Clustering algorithms Feature extraction partitioning algorithms Videos Social networking (online) Centroid based celestial clustering face clustering on large datasets optimization on clustering refined celestial PSO clustering

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A PARTITION AND RESYNTHESIS APPROACH TO TESTABLE DESIGN OF LARGE CIRCUITS

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 1995年第10期14卷 1268-1276页

作者： KANJILAL, S CHAKRADHAR, ST AGRAWAL, VD RUTGERS STATE UNIV DEPT COMP SCI NEW BRUNSWICK NJ 08903 USA NEC USA C&C RES LABS PRINCETON NJ 08540 USA AT&T BELL LABS MURRAY HILL NJ 07974 USA

We present a new area-efficient procedure for embedding test function into the gate-level implementation of a sequential circuit. First, we develop a test machine embedding technique for a given gate-level implementation of a finite state machine. The test machine states are mapped onto the states of the given circuit such that a minimum number of new state variable dependencies are introduced. The composite function is optimized, Experimental results show that our method yields testable machine implementations that have lower area than the corresponding full scan designs. The test generation complexity for our machine implementation is the same as that for a full scan design, To apply the method to large gate-level designs, we partition the circuit into interconnected finite-state machines, Each component state machine can be specified either as its gate-level implementation or as the extracted state diagram, We incorporate test functions into each component finite state machine such that the entire interconnection of the augmented components has the same testability properties as the product machine with a single test function, ISCAS '89 benchmark circuits are partitioned into component finite state machines using a new testability-directed partitioning algorithm. Again, our embedding procedure results;in testable circuits that have lower area than the corresponding full scan designs.

关键词： Circuit testing Logic testing Automata Integrated circuit interconnections Circuit synthesis Sequential analysis Sequential circuits Flip-flops partitioning algorithms Logic circuits

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PIPELINE ARCHITECTURES FOR RECURSIVE MORPHOLOGICAL OPERATIONS

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1995年第1期4卷 11-18页

作者： SHIH, FY KING, CT PU, CC NEW JERSEY INST TECHNOL DEPT ELECT & COMP ENGNNEWARKNJ 07102 NATL TSING HUA UNIV DEPT COMP SCIHSINCHU 300TAIWAN NEW JERSEY INST TECHNOL COMP VIS LABNEWARKNJ 07102 MING HSIN INST TECHNOL DEPT INFORMAT MANAGEMENTHSINCHUTAIWAN

In this paper, we introduce efficient pipeline architectures for the recursive morphological operations. The standard morphological operation is applied directly on the original input image and produces an output image. The order of image scanning in which the operator is applied to the input pixels is irrelevant. However, the intent of the recursive morphological operations is to feed back the output at the current scanning pixel to overwrite its corresponding input pixel to be considered into computation at the following scanning pixels. The resultant output image by recursive morphology inherently depends on the image scanning sequence. Two pipelined implementations of the recursive morphological operations are presented. The design of an application-specific systolic array is first introduced. The systolic array uses 3 n cells to process an n x n image in 6 n - 2 cycles. The cell utilization rate is 100%. Second, a parallel program implementing the recursive morphological operations and running on distributed-memory multicomputers is described. Performance of the program can be finely tuned by choosing appropriate partition parameters.

关键词： Pipelines Morphological operations Morphology Computer architecture Gray-scale Shape Image processing Systolic arrays partitioning algorithms Mathematics

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A MILP Based Framework for the Hydro Unit Commitment Considering Irregular Forbidden Zone Related Constraints

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IEEE TRANSACTIONS ON POWER SYSTEMS 2021年第3期36卷 1819-1832页

作者： Zhao, Zhipeng Cheng, Chuntian Liao, Shengli Li, Yapeng Lu, Quan Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China Dalian Univ Technol Key Lab Ocean Energy Utilizat & Energy Conservat Minist Educ Dalian 116024 Peoples R China Dalian Univ Technol Dept Elect & Elect Engn Dalian 116024 Peoples R China

The irregular forbidden zone (FZ) is a common phenomenon with giant hydropower plants developed in the past two decades in China. Irregular shapes of FZs significantly challenge hydro unit commitment (HUC). This paper proposes a novel MILP based framework for HUC considering irregular FZ related constraints including the FZ constraint, effects of linearization errors in both the net head and the output, and the FZ crossing constraint. In the framework, the FZ constraint is handled by the optimal convex partitioning algorithm and the common structure-based formulation method. Inspired by the planar translating robot placement problem, linearization errors are considered by the Minkowski sum method. To handle the FZ crossing constraint, we then propose a graph theory-based approximate formulation method. The framework is integrated into a HUC model with an objective of peak shaving. The model is then tested with a batch of real-world instances of a cascade hydropower system formed by ten giant units with highly irregular FZs. The results show our framework can effectively consider the irregular FZ related constraints. The major advantage of our framework is its ability to handle the irregular shapes of FZs without any tedious and error-prone manual processing.

关键词： Hydroelectric power generation Shape Vibrations partitioning algorithms Robots Reservoirs irregular forbidden zone hydro unit commitment MILP convex partition graph theory

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A Distributed Higher-Order k-Medoids Clustering Algorithm for Network Partition

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第5期11卷 4181-4193页

作者： Mo, Yuanqiu Xing, Ran Hou, Huazhou Southeast Univ Nanjing 211189 Peoples R China Univ Sydney Sydney NSW 2006 Australia Purple Mt Labs Nanjing 211102 Peoples R China

In this paper, we develop a distributed higher-order k-medoids clustering algorithm for networks using hop count as the distance metric, typical examples include social networks, wireless sensor networks and etc. Different than the classical k-medoids clustering where each cluster is assigned with one medoid (representative nodes in the network), the proposed algorithm is capable of partitioning the nodes into clusters dominated by multiple medoids. In this algorithm, a higher-order shortest path algorithm is first adopted to assign each node the clustering set comprising of its h (h >= 1) closest medoids using the hop count metric, then an aggregation algorithm collects the local information from each node to the medoids in its clustering set, based on which a medoids update mechanism helps each medoid decide whether to keep its medoid status or assign the status to one of its neighbors, so as to improve the clustering quality. The clustering performance of the proposed algorithm is proved to monotonically converge to a local optimum after running the algorithm finite times. Simulations results show that the proposed algorithm can achieve superior performance compared with several centralized $k$-medoids clustering algorithms and scale well as the number of nodes increases.

关键词： Clustering algorithms partitioning algorithms Length measurement Wireless sensor networks Social networking (online) Search problems Prototypes k -medoids clustering higher-order clustering graph algorithms

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A Formal Framework for Maximum Error Estimation in Approximate Logic Synthesis

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 2022年第4期41卷 840-853页

作者： Scarabottolo, Ilaria Ansaloni, Giovanni Constantinides, George A. Pozzi, Laura Univ Svizzera Italiana Fac Informat CH-6904 Lugano Switzerland Ecole Polytech Fed Lausanne EPFL Embedded Syst Lab CH-1015 Lausanne Switzerland Imperial Coll London Dept Elect & Elect Engn London SW7 2AZ England

Approximate logic synthesis techniques have become popular in error-resilient systems, where accuracy requirements can be traded for improved energy efficiency. Many of these techniques operate on a circuit by substituting or removing some of its portions under a predefined error constraint;however, the research on systematic methods to determine the error induced by such transformations is still at an early stage. We propose herein a generic framework for modeling maximum error in a circuit, called partition and propagate, which is a fundamental preliminary step for ALS. This framework is based on circuit partitioning and error propagation among the subcircuits. We provide a sound, complete formal description of such framework, and we illustrate how two state-of-the-art algorithms can be subsumed by it. Moreover, we propose a novel gate-level error-modeling algorithm, which is able to identify the whole range of possible errors induced by a given approximate transformation. We compare the three strategies and illustrate the efficiency of the new error-propagation methodology, which is able to identify accurate error bounds and, hence, guide ALS techniques to more valuable solutions.

关键词： Integrated circuit modeling Logic gates partitioning algorithms Computational modeling Approximation algorithms Scalability Monte Carlo methods Approximate computing efficient architecture error modeling hardware design logic synthesis

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MODELING AND CONTROL OF CARBON-MONOXIDE CONCENTRATION USING A NEURO-FUZZY TECHNIQUE

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 1995年第3期3卷 271-279页

作者： TANAKA, K SANO, M WATANABE, H HIROSHA CITY UNIV DEPT COMP SCIHIROSHIMA 73131JAPAN MERCURY TECHNOL NEW YORKNY 10005

Modeling and control of carbon monoxide (CO) concentration using a neuro-fuzzy technique are discussed. A self-organizing fuzzy identification algorithm (SOFIA) for identifying complex systems such as CO concentration is proposed. The main purpose of SOFIA is to reduce the computational requirement for identifying a fuzzy model. In particular, we simplify a procedure for finding the optimal structure Of fuzzy partition. The delta rule, which is a basic learning method in neural networks, is used for parameter identification of a fuzzy model. SOFIA consists of four stages which effectively realize structure identification and parameter identification. The procedure of SOFIA is concretely demonstrated by a simple example which has been used in some modeling exercises. The identification result shows effectiveness of SOFIA. Next, we apply SOFIA to a prediction problem for CO concentration in the air at the busiest traffic intersection in a large city of Japan. Prediction results show that the fuzzy model is much better than a linear model. Furthermore, we simulate a control system for keeping CO concentration at a constant level by using the identified fuzzy model. A self-learning for adaptively modifying controller parameters by delta rule is introduced because the dynamics of real CO concentration system changes gradually over a long period of time. Two self-learning controllers are designed in this simulation, One is a self-learning linear PI controller. The other is a self-learning fuzzy PI controller. We investigate robustness and adaptability of this control system for disturbance and parameter perturbation of the CO concentration model. Simulation results show that the self-learning fuzzy controller is more robust and adaptive.

关键词： Fuzzy control Fuzzy systems Parameter estimation Predictive models Control system synthesis Robust control partitioning algorithms Learning systems Neural networks Fuzzy neural networks

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