2009 CS Technical Reports

• CS-2009-01 Tamir Levi and Ami Litman: On Fast Bitonic Sorting Networks
• CS-2009-02 Michael Kaminski and Tony Tan: A note on two-pebble automata over infinite alphabets
• CS-2009-03 Tony Tan: Graph Reachability and Pebble Automata over Infinite Alphabets
• CS-2009-04 Tony Tan: A Logic for Graph with the Edges as the Domain
• CS-2009-05 Tony Tan: On Pebble Automata for Data Languages with Decidable Emptiness Problem
• CS-2009-06 Ilan Gronau: Bayesian Analysis Of Distance Estimation in the K2P Model.
• CS-2009-07 Tamir Levi and Ami Litman: Lower Bounds On Bitonic Sorting Networks
• CS-2009-08 Eliyahu Osherovich, Michael Zibulevsky, and Irad Yavneh: IMAGE RECONSTRUCTION FROM NOISY FOURIER MAGNITUDE WITH PARTIAL PHASE INFORMATION
• CS-2009-09 Eliyahu Osherovich, Michael Zibulevsky, and Irad Yavneh: Signal Reconstruction From The Modulus of its Fourier Transform
• CS-2009-10 Tony Tan: Determinizing two-way alternating pebble automata for data languages
• CS-2009-11 Ilan Gronau, Shlomo Moran and Irad Yavneh: Adaptive Distance Measures for Resolving K2P Quartets: Metric Separation versus Stochastic Noise
• CS-2009-12 Eliyahu Osherovich: Designing Optimal Projections for Compressed Sensing: Algorithm Comparison
• CS-2009-13 Ron Rubinstein, Michael Zibulevsky, Michael Elad: Learning Sparse Dictionaries for Sparse Signal Approximation
• CS-2009-14 Yael Meller, Orna Grumberg and Sharon Shoham: A Framework For Compositional Verification of Multi-Valued Systems Via Abstraction-Refinement
• CS-2009-15 Tamar Aizikowitz and Michael Kaminski: Linear Conjunctive Grammars and One-turn Synchronized Alternating Pushdown Automata
• CS-2009-16 Eliyahu Osherovich, Michael Zibulevsky, and Irad Yavneh: Fast Reconstruction Method for Diffraction Imaging
• CS-2009-17 Michael Zibulevsky: How to relax an economic crisis using consumer insurance obligations
• CS-2009-18 Michael Zibulevsky: How to prevent economic crisis in time of disaster: consumer insurance bonds
• CS-2009-19 Avishai Adler and Michael Zibulevsky: Sparse Solution for the Intensity-Modulated Radiotherapy Problem Using Conic Programming