~~
Speaker: Ilya Poltorak, 
M.Sc. student under the supervision of Prof. Anthony Weiss

Wednesday, January 20th, 2016 at 15:30
Room 011, Kitot Bldg., Faculty of Engineering

A Study of Source Localization Using Carrier Phase

Abstract

Consider a moving receiver, continuously tracking the carrier phase of a continuous wave signal, produced by a static emitter.
We propose a highly accurate method (order of magnitude of the signal wavelength) for localizing the emitter, using search based as well as closed form methods.
Moreover, we analyze the effect of various challenges to this localization method, such as carrier frequency uncertainty, phase modulation, cycle slips - significant errors introduced by inaccuracies in the phase measurement mechanism and receiver location uncertainties.
We propose a maximum likelihood algorithm that mitigates the carrier frequency uncertainty effect and an "autofocus" method that overcomes the receiver location uncertainties, utilizing emitters of opportunity.
According to our analysis, the cycle slips pose the most significant challenge to the proposed method, as other effects can be mitigated or result in a significantly smaller degradation on the localization accuracy.
The performance of the algorithms is validated analytically and numerically by the Cramer Rao Lower Bound, by small error variance derivations and by Monte-Carlo simulations.

~~(The talk will be given in English)

Speaker:     Dr. Aharon Bar Hillel
   Microsoft Research, Israel

Monday, January 18th, 2016
15:00 - 16:00
Room 011, Kitot Bldg., Faculty of Engineering
Large scale feature selection for visual representation learning

Abstract
Training accurate visual classifiers from large data sets critically depend on learning the right representation for the problem. In this talk, I will discuss a representation learning framework based on an iterative interaction of two components: a feature generator suggesting candidate features, and a feature selector choosing among them. In the feature selector role, I will present a feature selection algorithm for Support Vector Machines (SVMs) enabling selection among hundreds of thousands of features, while maintaining the accuracy of computationally expensive wrapper methods. For the feature generator, I will discuss two main examples: part-based feature generation for human detection, and sparse feature generation for object recognition under severe test-time speed constraints. In both examples state of the art classifiers (at the time of submission) were learned. Specifically the sparse classifiers are currently the state of the art for visual classification with a tight computational budget. 

Speaker's bio:
Aharon Bar Hillel is a researcher at Microsoft Research ATLI (Advanced Technical Labs Israel) since 2012. He received his Ph.D from The Hebrew University of Jerusalem in 2006, focusing on machine learning and computer vision. Since then he has been doing machine learning and computer vision oriented research at Intel Research (2006-2008) and at GM Research (2009-2012). He is interested in learning representation for machine learning tasks, including distance function learning, feature selection and synthesis, and deep learning.

~~(The talk will be given in English)

Speaker:       Dr. Ronit Bustin
                        EE, TAU

Sunday, January 17th, 2016
15:00 - 16:00
Room 011, Kitot Bldg., Faculty of Engineering
The SNR-Evolution of the MMSE of Codes

Abstract:
In this talk we present the concept of the SNR-evolution of the minimum mean-square error (MMSE) of code sequences. This concept leads us to a new approach in the investigation of the long standing open problem of the two-user Gaussian interference Channel.
We begin by examining the I-MMSE trade-off problem, where the goal is to maximize the rate to one receiver, while at the same time limiting the disturbance on some unintended receiver. The disturbance is measured in term of the MMSE at that additional (unintended) receiver. The optimization problem is a simplification of the intereference channel problem, in the sense that here we consider only a single transmitter. Nonetheless, its analysis provides strong support for the best known achievability scheme - the Han-Kobayashi scheme. Motivated by this result, we turned to examine the two-user Gaussian interference channel problem, where simultaneous transmissions from two users interfere with each other. Using the SNR-evolution approach, we were able to resolve the Costa Conjecture for bounded variance inputs, a.k.a the missing corner points conjecture.
We've demonstrated the usefulness of SNR-evolution in capacity problems, where blocklength goes to infinity. As such our goal is to extend the approach to the finite blocklength regime.
Recently we have been exploring the SNR-evolution of the MMSE of finite inputs in the maximization of the MMSE at one SNR point, given an MMSE constraint at a different SNR point. Our result recover the known limiting expressions for the I-MMSE trade-off problem.
The key technical novelty used here is a new upper bound on the MMSE. This new bound allows to bound the MMSE for all SNR values below a certain SNR at which the MMSE is known (which corresponds to the disturbance constraint). This new bound complements the “single-crossing property” of the MMSE that upper bounds the MMSE for all SNR values above a certain value at which the MMSE value is known. The new MMSE upper bound provides a refined characterization of the phase-transition phenomenon which manifests, in the limit as the block-length goes to infinity, as a discontinuity of the MMSE for the problem at hand. Finally, a matching lower bound to within an additive gap of the order of O( log log( SNR ) ), achieved by “mixed inputs”, gives new insights to the properties required form the optimal inputs.‏

Bio:
Ronit Bustin received a B.Sc. degree in electrical engineering and computer science and a M.Sc. degree in electrical engineering in 2004 and 2006, respectively, from Tel-Aviv university, Israel. She received a Ph.D. in electrical engineering in 2013 from the the Technion - Israel Institute of Technology, Haifa. From 2013 to 2015 she was a postdoctoral research associate in the department of electrical engineering at Princeton University. She is currently a postdoctoral research associate in the department of electrical engineering at Tel Aviv University. Her research interests include multi-user information theory, secrecy constraints, Gaussian MIMO channels, estimation theory, channel coding, interactive communication and communication complexity. Ronit Bustin received the Irwin and Joan Jacobs scholarship for excellence in graduate studies and research, in January 2010. She is a recipient of the Adams fellowship from the Israel Academy of Sciences and Humanities, April 2010, and an Andrew and Erna Finci Viterbi graduate fellow in the faculty of electrical engineering at the Technion for the fall semester 2010-2011. Ronit received the Rothschild fellowship in 2013 and the women postdoctoral scholarship of Israel’s Council for Higher Education (VATAT) for her post-doctoral studies at Princeton.

~~(The talk will be given in English)

Speaker:     Dr. Eli Brookner
    RAYTHEON CO. (Retired)

Sunday, January 24th, 2016
15:00 - 16:00
Room 011, Kitot Bldg., Faculty of Engineering

Advances and Breakthroughs in Radar and Phased Arrays

Abstract
New systems: S/X-band AMDR: GaN AESA, 30 times sensitivity and tracks as SPY-1D(V).  3, 4, 6 faced “Aegis” systems: USA, Israel, China, Signaal-Thales, Japan, Australia.  System Upgrade: Patriot now 2016 state-of –art radar, GaN Active Electronically Scanned Array (AESA), 360o coverage without rotating antenna; Low Cost Packaging: Using Commercial Off-the-Shelf (COTS) components; Extreme MMIC: 32 element 60 GHz T/R array on chip, future cost few dollars. Digital Beam Forming (DBF): A/D for every element: Elta (Israel), CEA (Australia), Thales (France), Raytheon developing mixer-less direct RF A/D having >400 MHz instantaneous bandwidth, reconfigurable between S and X-band. Materials: GaN can put 5X to 10X power of GaAs in same footprint, 38% less costly, 100 million hr MTBF. MIMO (Multiple Input Multiple Output): Where it makes sense and how conventional arrays can do as well. Metamaterial Antennas: $1K (goal) 20 GHz and 30 GHz ESAs. Very Low Car Array Radar: $100s. MEMS: for Phase shifters and flying insect robots;  Printed Electronics: Low cost 1.6 GHz printed diodes  (goal 2.4 GHz).  Electrical and Optical Signals on Same Chip; IR transparent in silicon. Graphene and Carbon Nanotube (CNT): Potential for Terahertz transistor clock speeds, Moore’s Law marches on; Spintronics: Could revolutionize computer architecture away from John von Neumann model. Memristors: Allow one to do what human brain does in a shoe box instead of city sized computer. Biodegradable Arrays of Transistors or LEDs: Imbedded under skin for detecting cancer or low glucose. Quantum Radar: See stealth targets.
     
Bio:  BSc City College of New York, DrSc from Columbia University ’62.
Worked on marine, Air Traffic Control, ballistic missile defense, space radars and phased arrays at Raytheon 1962-2015 (retired). 1952-1962 at: Columbia University, Nicolet, Rome AF Lab. IEEE 2006 Dennis Picard Medal for Radar Technology & Application; IEEE ’03 Warren White Award; 1966 Journal of Franklin Institute Premium Best Paper Award; 1998 Best Applications Paper IEEE Wheeler Prize. Fellow: IEEE, AIAA, MSS. 4 popular books on radar, arrays, tracking. Gave courses to >10,000 in 25 countries. Banquet/keynote speaker 13 times. >230 papers, talks, correspondences of which >100 invited. 6 papers in Books of Reprints. Contributed chapters to three books. 9 patents.