Computational Intelligence in Digital and Network Designs and Applications

This book explains the application of recent advances in computational intelligence algorithms, design methodologies, and synthesis techniques to the design of integrated circuits and systems. It highlights new biasing and sizing approaches and optimization techniques and their application to the design of high-performance digital, VLSI, radio-frequency, and mixed-signal circuits and systems. This second of two related volumes addresses digital and network designs and applications, with 12 chapters grouped into parts on digital circuit design, network optimization, and applications. It will be of interest to practitioners and researchers in computer science and electronics engineering engaged with the design of electronic circuits.

[1]  Peng Sun,et al.  A Robust Optimization Perspective on Stochastic Programming , 2007, Oper. Res..

[2]  David K. Gifford,et al.  Static dependent costs for estimating execution time , 1994, LFP '94.

[3]  Hongyuan Zha,et al.  Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence Towards Effective Prioritizing Water Pipe Replacement and Rehabilitation ∗ , 2022 .

[4]  Felipe Albertao,et al.  Incremental dictionary learning for fault detection with applications to oil pipeline leakage detection , 2011 .

[5]  Matthew W. Tanner,et al.  A General Heuristic Method for Joint Chance-Constrained Stochastic Programs with Discretely Distributed Parameters , 2008 .

[6]  Laurent El Ghaoui,et al.  Robust Solutions to Uncertain Semidefinite Programs , 1998, SIAM J. Optim..

[7]  Marco C. Campi,et al.  A Sampling-and-Discarding Approach to Chance-Constrained Optimization: Feasibility and Optimality , 2011, J. Optim. Theory Appl..

[8]  Darinka Dentcheva,et al.  Bounds for probabilistic integer programming problems , 2002, Discret. Appl. Math..

[9]  R. Jagannathan,et al.  Chance-Constrained Programming with Joint Constraints , 1974, Oper. Res..

[10]  Füsun Özgüner,et al.  Run-time statistical estimation of task execution times for heterogeneous distributed computing , 1996, Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing.

[11]  Junchi Yan,et al.  Weighted sparse coding residual minimization for visual tracking , 2011, 2011 Visual Communications and Image Processing (VCIP).

[12]  S. Ranji Ranjithan,et al.  Chance-constrained genetic algorithms , 1999 .

[13]  Yin Li,et al.  An Accelerated Human Motion Tracking System Based on Voxel Reconstruction under Complex Environments , 2009, ACCV.

[14]  Jean A. Peperstraete,et al.  Cycle-static dataflow , 1996, IEEE Trans. Signal Process..

[15]  Benoît Dupont de Dinechin,et al.  A clustered manycore processor architecture for embedded and accelerated applications , 2013, 2013 IEEE High Performance Extreme Computing Conference (HPEC).

[16]  A. Charnes,et al.  Chance-Constrained Programming , 1959 .

[17]  Mateusz Zotkiewicz,et al.  Robust routing and optimal partitioning of a traffic demand polytope , 2011, Int. Trans. Oper. Res..

[18]  Bin Li,et al.  A Self-adaptive Mixed Distribution Based Uni-variate Estimation of Distribution Algorithm for Large Scale Global Optimization , 2009, Nature-Inspired Algorithms for Optimisation.

[19]  Dimitris Bertsimas,et al.  Robust optimization with simulated annealing , 2010, J. Glob. Optim..

[20]  Giuseppe Carlo Calafiore,et al.  Uncertain convex programs: randomized solutions and confidence levels , 2005, Math. Program..

[21]  Dritan Nace,et al.  A GRASP for Placement and Routing of Dataflow Process Networks on Many-Core Architectures , 2013, 2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing.

[22]  Luca Benini,et al.  P2012: Building an ecosystem for a scalable, modular and high-efficiency embedded computing accelerator , 2012, 2012 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[23]  Denis Barthou,et al.  Study of Variations of Native Program Execution Times on Multi-Core Architectures , 2010, 2010 International Conference on Complex, Intelligent and Software Intensive Systems.

[24]  Bin Li,et al.  Estimation of distribution and differential evolution cooperation for real-world numerical optimization problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[25]  Dritan Nace,et al.  The robust binomial approach to chance-constrained optimization problems with application to stochastic partitioning of large process networks , 2014, J. Heuristics.

[26]  Bin Li,et al.  Estimation of distribution and differential evolution cooperation for large scale economic load dispatch optimization of power systems , 2010, Inf. Sci..

[27]  Patrizia Beraldi,et al.  Beam search heuristic to solve stochastic integer problems under probabilistic constraints , 2005, Eur. J. Oper. Res..

[28]  Loïc Cudennec,et al.  Throughput Constrained Parallelism Reduction in Cyclo-static Dataflow Applications , 2013, ICCS.

[29]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[30]  D. Nace,et al.  A heuristic algorithm for stochastic partitioning of process networks , 2012, 2012 16th International Conference on System Theory, Control and Computing (ICSTCC).

[31]  Edward A. Lee,et al.  Dataflow process networks , 2001 .

[32]  David Wentzlaff,et al.  Processor: A 64-Core SoC with Mesh Interconnect , 2010 .

[33]  Gilles Kahn,et al.  The Semantics of a Simple Language for Parallel Programming , 1974, IFIP Congress.

[34]  Xin Yao,et al.  Pipe failure prediction: A data mining method , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).

[35]  M. Wendt,et al.  Robust model predictive control under chance constraints , 2000 .

[36]  Timothy Mattson,et al.  A 48-Core IA-32 message-passing processor with DVFS in 45nm CMOS , 2010, 2010 IEEE International Solid-State Circuits Conference - (ISSCC).

[37]  R. F. Freund,et al.  Optimal selection theory for superconcurrency , 1989, Proceedings of the 1989 ACM/IEEE Conference on Supercomputing (Supercomputing '89).

[38]  Viktor K. Prasanna,et al.  Heterogeneous computing: challenges and opportunities , 1993, Computer.

[39]  Jian Liu,et al.  Visual saliency detection via rank-sparsity decomposition , 2010, 2010 IEEE International Conference on Image Processing.

[40]  Luca Benini,et al.  Stochastic allocation and scheduling for conditional task graphs in multi-processor systems-on-chip , 2010, J. Sched..

[41]  Rudy Lauwereins,et al.  Cyclo-static data flow , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[42]  Junchi Yan,et al.  Two-stage based ensemble optimization framework for large-scale global optimization , 2013, Eur. J. Oper. Res..

[43]  Alexander Shapiro,et al.  Sample Average Approximation Method for Chance Constrained Programming: Theory and Applications , 2009, J. Optimization Theory and Applications.

[44]  Melvyn Sim,et al.  The Price of Robustness , 2004, Oper. Res..

[45]  Alan Burns,et al.  A Probabilistic Framework for Schedulability Analysis , 2003, EMSOFT.

[46]  Jinkyu Lee,et al.  Online robust optimization framework for QoS guarantees in distributed soft real-time systems , 2010, EMSOFT '10.

[47]  Abdel Lisser,et al.  Knapsack problem with probability constraints , 2011, J. Glob. Optim..

[48]  András Prékopa Static Stochastic Programming Models , 1995 .

[49]  Arkadi Nemirovski,et al.  On Safe Tractable Approximations of Chance-Constrained Linear Matrix Inequalities , 2009, Math. Oper. Res..

[50]  Jakob Engblom,et al.  The worst-case execution-time problem—overview of methods and survey of tools , 2008, TECS.

[51]  Yu Wang,et al.  Self-adaptive learning based particle swarm optimization , 2011, Inf. Sci..

[52]  Chang-Gun Lee,et al.  Stochastic analysis of periodic real-time systems , 2002, 23rd IEEE Real-Time Systems Symposium, 2002. RTSS 2002..

[53]  Junchi Yan,et al.  Visual Saliency Detection via Sparsity Pursuit , 2010, IEEE Signal Processing Letters.

[54]  Xin Yao,et al.  Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..

[55]  Bin Li,et al.  Fixed-point digital IIR filter design using multi-objective optimization evolutionary algorithm , 2010, 2010 IEEE Youth Conference on Information, Computing and Telecommunications.

[56]  Darinka Dentcheva,et al.  Concavity and efficient points of discrete distributions in probabilistic programming , 2000, Math. Program..

[57]  Allen L. Soyster,et al.  Technical Note - Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming , 1973, Oper. Res..

[58]  Benoît Dupont de Dinechin,et al.  Periodic schedules for Cyclo-Static Dataflow , 2013, The 11th IEEE Symposium on Embedded Systems for Real-time Multimedia.

[59]  John L. Gustafson,et al.  Reevaluating Amdahl's law , 1988, CACM.

[60]  Jian Song,et al.  Model-based 3D human motion tracking and voxel reconstruction from sparse views , 2010, 2010 IEEE International Conference on Image Processing.

[61]  Walid Ben-Ameur,et al.  Routing of Uncertain Traffic Demands , 2005 .

[62]  Alexander Shapiro,et al.  Convex Approximations of Chance Constrained Programs , 2006, SIAM J. Optim..

[63]  Robert Tibshirani,et al.  An Introduction to the Bootstrap , 1994 .

[64]  Giuseppe Carlo Calafiore,et al.  The scenario approach to robust control design , 2006, IEEE Transactions on Automatic Control.

[65]  Ravishankar K. Iyer,et al.  Predictability of Process Resource Usage: A Measurement-Based Study on UNIX , 1989, IEEE Trans. Software Eng..

[66]  Petru Eles,et al.  Memory and time-efficient schedulability analysis of task sets with stochastic execution time , 2001, Proceedings 13th Euromicro Conference on Real-Time Systems.

[67]  Roberto Aringhieri,et al.  Solving Chance-Constrained Programs Combining Tabu Search and Simulation , 2004, WEA.

[68]  Yin Li,et al.  An Optimization Based Framework for Human Pose Estimation , 2010, IEEE Signal Processing Letters.

[69]  Bijay Baran Pal,et al.  A genetic algorithm based stochastic simulation approach to chance constrained interval valued multiobjective decision making problems , 2010, 2010 Second International conference on Computing, Communication and Networking Technologies.

[70]  René Henrion,et al.  Convexity of chance constraints with independent random variables , 2008, Comput. Optim. Appl..

[71]  David A. Patterson,et al.  Computer Architecture: A Quantitative Approach , 1969 .

[72]  Benoît Dupont de Dinechin,et al.  Extended Cyclostatic Dataflow Program Compilation and Execution for an Integrated Manycore Processor , 2013, ICCS.

[73]  Arkadi Nemirovski,et al.  Robust solutions of Linear Programming problems contaminated with uncertain data , 2000, Math. Program..

[74]  Renaud Sirdey,et al.  A Parallel Simulated Annealing Approach for the Mapping of Large Process Networks , 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum.

[75]  James R. Luedtke,et al.  A Sample Approximation Approach for Optimization with Probabilistic Constraints , 2008, SIAM J. Optim..

[76]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[77]  Arkadi Nemirovski,et al.  Robust optimization – methodology and applications , 2002, Math. Program..

[78]  Bin Li,et al.  Two-stage ensemble memetic algorithm: Function optimization and digital IIR filter design , 2013, Inf. Sci..

[79]  Bin Li,et al.  A restart univariate estimation of distribution algorithm: sampling under mixed Gaussian and Lévy probability distribution , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[80]  Bin Li,et al.  Two-stage based ensemble optimization for large-scale global optimization , 2010, IEEE Congress on Evolutionary Computation.

[81]  Yu Yang,et al.  Cooperative Coevolutionary Genetic Algorithm for Digital IIR Filter Design , 2007, IEEE Transactions on Industrial Electronics.

[82]  Shie Mannor,et al.  Optimization Under Probabilistic Envelope Constraints , 2012, Oper. Res..

[83]  Matthieu Lemerre,et al.  Equivalence between Schedule Representations: Theory and Applications , 2008, 2008 IEEE Real-Time and Embedded Technology and Applications Symposium.

[84]  Ming-Hsuan Yang,et al.  Contour detection via random forest , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[85]  R. Rockafellar,et al.  Optimization of conditional value-at risk , 2000 .

[86]  Yi Yang,et al.  Sequential Convex Approximations to Joint Chance Constrained Programs: A Monte Carlo Approach , 2011, Oper. Res..

[87]  George B. Dantzig,et al.  Linear Programming Under Uncertainty , 2004, Manag. Sci..