TIME/PLACE: Friday September 19 at 14:30 in EOW 430 SPEAKER: Andreas Antoniou TITLE: ABSTRACT:

NOTE: This order may need to be modified slightly from time to time due to absences, etc.. Peter Hampton(Supervisor: Pan Agathoklis) Wu-Sheng Lu Michael McGuire Diego Felix (Supervisor: Michael McGuire) Mohamed Yasein (Supervisor: Pan Agathoklis) Yihai Zhang (Supervisor: Wu-Sheng Lu and Aaron Gulliver) Deepali Arora (Supervisor: Pan Agathoklis) Eugene Hyun (Supervisor: Michael McGuire) Pan Agathoklis Ping Wan (Supervisor: Michael McGuire) Ze Dong (Supervisor: Michael Adams) Najith Liyanage (Supervisor: Pan Agathoklis) Michael Adams Diego Sorentino (Supervisor: Andreas Antoniou) Parameswaran Ramachandran (Supervisor: Wu-Sheng Lu and Andreas Antoniou) Ana Maria Sevcenco (Supervisor: Wu-Sheng Lu)

TIME/PLACE: Friday August 8 at 14:30 in EOW 430 SPEAKER: TITLE: ABSTRACT: CANCELLED TIME/PLACE: Thursday July 24 at 15:45 in EOW 430 SPEAKER: TITLE: ABSTRACT: CANCELLED DUE TO LACK OF SPEAKER TIME/PLACE: Friday July 11 at 14:30 in EOW 430 SPEAKER: TITLE: ABSTRACT: CANCELLED DUE TO LACK OF SPEAKER TIME/PLACE: Thursday 26 June at 15:45 in EOW 430 SPEAKER: TITLE: ABSTRACT: CANCELLED DUE TO LACK OF SPEAKER TIME/PLACE: Friday June 13 at 14:30 in EOW 430 SPEAKER: Deepali Arora TITLE: Addressing the hidden beam problem using a modified beamformer ABSTRACT: The advancements in antenna technology and their use in WLANs such as IEEE 802.11 has shown that the directional antennas are preferable over omni-directional antennas not only in terms of increased range, better directivity and substantial reduction in interference but also in large power savings which is a critical issue in wireless systems. However, when used in IEEE 802.11 systems that are based on carrier sensing, directional antennas present their own share of issues such as the hidden node problem, the hidden beam problem and deafness. In this seminar a new method to deal with the hidden beam problem in CSMA based systems will be presented. The method is based on a modification of the beamformer weights to reduce null depths of an original beam. The differences in the original and modified beam patterns are quantified in terms of half power beam width (HPBW) and directivity which shows that the modified beam yields significant improvements in null reduction with relatively small changes to directivity and HPBW. The performance of the modified beam obtained is compared with that of a original beam in terms of reducing hidden beam problem when used in non-persistent CSMA systems. The proposed methodology is simple and effective in solving the hidden beam problem. TIME/PLACE: Thursday May 29 at 15:45 in EOW 430 SPEAKER: Yihai Zhang TITLE: Blind Polynomial Channel Estimation for OFDM Systems ABSTRACT: Orthogonal frequency division multiplexing (OFDM) modulation is widely used in communication systems to meet the demand for ever increasing data rates.Characteristics of the transmitted signal can be employed for blind channel identification. We propose a blind polynomial channel estimation algorithm using noncircular second-order statistics of the received OFDM signal. A set of polynomial equations are then formulated based on the correlation of the received signal. The solution of these equations provides an estimation of the channel coefficients. Results are presented which show that the proposed algorithm provides performance comparable to LMMSE with lower computational complexity. The performance is near-optimal for large OFDM systems. TIME/PLACE: Friday May 16 at 14:30 in EOW 430 SPEAKER: Ana-Maria Sevcenco TITLE: Medical image segmentation based on adaptive thresholding, morphological operations and level set methods ABSTRACT: Image segmentation of multiple regions plays a critical role in a variety of image analysis and visualization tasks. Segmentation can be achieved by several methods such as clustering, histogram-based methods, edge detection, region growing techniques, level set methods, and multi-scale segmentation. It is not surprising that performance enhancement can be achieved by appropriately combining some of these techniques. In this talk we present two algorithms for liver segmentation -- an important task in the development of computer-aided multi-phase CT diagnosis system for tumor identification in liver. The first algorithm is an integrated liver segmentation method based on adaptive thresholding techniques, morphological operations and edge detection, where image's local intensity is used as a similarity measure for region segmentation. The second algorithm employs in addition a level-set framework for a more accurate segmentation and region identification. Both algorithms are successfully tested on a set of 98 real CT scan images. We present some of the experimental results and a performance analysis to illustrate the efficiency of the proposed segmentation methods. TIME/PLACE: Friday May 2 at 14:30 in EOW 430 SPEAKER: Parameswaran Ramachandran TITLE: ABSTRACT: TIME/PLACE: Friday April 18 at 14:30 in EOW 430 SPEAKER: Diego Sorrentino TITLE: Multiframe Image Super-Resolution Using Quasi-Newton Algorithms ABSTRACT: Multiframe image super-resolution algorithms can be used to reconstruct a high-quality high-resolution image from several warped, blurred, undersampled, and possibly noisy images acquired from the same scene. A widely used means of implementing such algorithms is by optimization-based model inversion. In the past, steepest-descent methods have been applied. Nonetheless, while easy to implement, these methods are known for their poor convergence properties and for being sensitive to numerical ill-conditioning. In this talk, we show how the multiframe super-resolution problem can be tackled using powerful quasi-Newton algorithms and provide details on efficient implementations that are well suited given the large scale nature of the problem. In addition, we present results of preliminary testing that indicate a significant improvement in terms of convergence speed with respect to steepest-descent implementations. TIME/PLACE: Friday April 4 at 14:30 in EOW 430 SPEAKER: Michael McGuire TITLE: Bounds on MSE for Non-Linear Estimation Problems ABSTRACT: An important issue for parameter estimation problems is to determine if the desired level of accuracy is achievable with the available measurements. For this lower bounds on the mean square error (MSE) of the estimator are often employed. The most popular lower bound is the Cramer-Rao lower bound. This bound assumes only the measurements are used to estimate the parameters of interest. Prior information on the parameter values of interest is not included in the bound calculation. The Cramer-Rao lower bounds also has required regularity conditions which are often violated in non-linear estimation problems. In this talk, we will discuss more general lower bounds on the MSE such as the Bayesian Cramer-Rao, Weinstein-Weiss and extended Ziv-Zakai lower bounds. These bounds account for prior information in the estimation process and can handle general measurement models. Conditions will be demonstrated when these bounds are tight to actual estimator performance. This talk will also discuss the use of these bounds for model-based estimation approaches such as the use of Extended Kalman filters and particle filters to estimate parameters of an evolving process from measurements made at different times. The extension of the standard estimation lower bounds to these cases will be demonstrated. Some of the more common cases where this extension can go wrong are also discussed. TIME/PLACE: Wednesday March 19 at 15:45 in EOW 430 SPEAKER: Wu-Sheng Lu TITLE: Linear updates by SOCP for power symmetric perfect reconstruction filter banks ABSTRACT: Two-channel power-symmetric FIR filter banks are among the most popular building blocks for multirate systems as they offer precise perfect reconstruction (PR) property. Many design methods for this class of filter banks have been proposed since early 1980s. This talk gives a brief review of several important design methods with comments, and describes a new method. The new method is based on a linear updating strategy that can be readily realized with a second-order cone programming (SOCP) solver. We apply this technique to deduce two design formulations, one with a least squares objective function and the other with a minimax criterion. Examples are supplied to help examine design performance and efficiency. TIME/PLACE: Friday March 7 at 14:30 in EOW 430 SPEAKER: Diego Sorrentino TITLE: Image Super-Resolution, an Overview ABSTRACT: As the number of digital imaging based applications grows, so does the demand for higher quality images. Applications like surveillance, remote sensing, and medical imaging greatly benefit from the availability of high quality high resolution (HR) images. The usual approach to obtain higher resolution images implies building systems with higher pixel count sensors. Unfortunately, this trend is reaching a technological limit by which sensors pixel count cannot be increased without severely degrading their overall quality. One promising strategy to build systems that acquire HR images using inexpensive low-resolution (LR) sensors is by resorting to signal processing techniques known as 'Super-Resolution' (SR). SR algorithms exploit the availability of several LR images from the same scene to reconstruct a high quality HR version of it. In this talk we provide an introduction to image super-resolution, as well as an overview of some the most prominent techniques. TIME/PLACE: Friday February 22 at 14:30 in EOW 430 SPEAKER: TITLE: ABSTRACT: Rescheduled due to reading break. TIME/PLACE: Friday February 8 at 14:30 in EOW 430 SPEAKER: Peter Hampton TITLE: A new wave-front reconstruction method for adaptive optics systems using wavelets ABSTRACT: A new technique for wave-front reconstruction from gradient measurements is presented. This technique is based on obtaining the Haar wavelet image decomposition of the original image by appropriate filtering of the gradient measurement data. The proposed technique is illustrated with an example and its reconstruction accuracy and the influence of the input SNR are discussed. Results indicate that the proposed technique is a computationally efficient and accurate technique for image reconstruction from gradient measurements. TIME/PLACE: Thursday January 24 at 15:45 in EOW 430 SPEAKER: Najith Liyanage TITLE: Spectral Characteristics of 3D Windowed and Sampled Linear Trajectory(LT) Space-Time Signals ABSTRACT: Linear Trajectory Signals(LT) are an especially important class of MD signals. They occur in many kinds of signal processing sytems, including television, radar and seismic signal processing. An MD signal is a LT signal if there exist a constant MD vector n such that the directional derivative of the LT signal along n is zero everywhere in the domain of the signal. In this talk we focus on a special LT signal with a square object. First, the Region of Support (ROS) of the spectrum of such a Linear Trajectory (LT) signal and how it deviates from the ideal spectrum due to practical processes 2D windowing and 3D spatio-temporal sampling are discussed. Then, their ROS of the spectra are algebraically analyzed based on the changes of parameters such as the speed of the object, the sample rates and the window size. Finally, the algebraically explained characteristics of the ROS of the spectra are simulated and verified using Matlab. TIME/PLACE: Friday January 11 at 14:30 in EOW 430 SPEAKER: TITLE: ABSTRACT: *** CANCELLED **** TIME/PLACE: Friday December 7 at 14:30 in EOW 430 SPEAKER: Ping Wan TITLE: Channel Estimation for OFDM in Fast Fading and Frequency Selective Channels ABSTRACT: Orthogonal frequency-division multiplexing (OFDM) is an efficient technique for high data rate transmission in wireless communications. A cyclic prefix (CP) is inserted at the transmitter and removed at the receiver. If the length of CP is equal to or long than the delay spread of the channel, intersymbol interference (ISI) due to multipath propagation is eliminated. In slow fading channels, the channel is stationary over one OFDM symbol, a simple one-tap equalizer can be employed. However, in fast fading channels, the channel is variant over the period of an OFDM symbol, the orthogonality between subcarriers is destroyed, resulting in intercarrier interference (ICI) which impacts the bit-error rate (BER) performance. To mitigate ICI, channel equalization schemes are employed which rely on accurate channel estimation. The channel is estimated using pilot symbol assisted modulation (PSAM). In fast fading channels, due to the interference from the neighboring symbols in the frequency domain, pilot symbols are inserted in the time domain. By taking the traditional Rayleigh fading channel into account, several channel estimators have been derived such as the linear minimum mean square error (LMMSE) estimator and the least squares (LS) estimator. In order to get low-complexity equalizers in the fast fading channel, the basis expansion model (BEM) with a low number of parameters is employed to approximate the channel such as the oversampled BEM, the Slepian BEM and the optimal BEM, where only the BEM coefficients are estimated. For the oversampled and Slepian BEM, the coefficients are estimated by the LS estimator. We propose a now optimal BEM where the coefficients are estimated by the LMMSE approach. The proposed model minimizes the mean squared LS estimator error for a fixed number of parameters. This model is also robust when the Doppler frequency is varied from the design value. Simulation results show the channel estimation based on the optimal BEM improves the BER performance with a low computational cost. Use of a parameter model allows the use of a Kalman filter to estimate the channel in the fast fading. A dynamic model based on the evolution of the BEM parameters in sequential time segments of the channel is presented for OFDM systems in fast fading channels. TIME/PLACE: Thursday November 8 at 15:45 in EOW 430 SPEAKER: Mohamed Yassein TITLE: An Image Normalization Technique based on Geometric Properties of Image Feature Points ABSTRACT: Image normalization techniques have been used as a preprocessing step in many applications such as pattern recognition and classification, image retrieval, and image watermarking. Image normalization is used in such applications with the purpose of representing objects, patterns (or the entire image) regardless of changes in their orientation, size, or position. This talk will introduce a technique for image normalization based on the geometric properties of image feature points. The proposed technique consists of two main steps, feature point extraction and estimating the normalization parameters. The feature point extraction is carried out using an extractor that based on scale-interaction of Mexican-hat wavelets. The locations of the extracted feature points are used to estimate the normalization parameters needed for normalizing the image. The proposed technique can be used to normalize input images in a rotation, translation and scale invariant manner. Experimental results illustrate the accuracy of normalization and the robustness against several geometric distortions, image degradations and common image-processing operations. TIME/PLACE: Friday November 23 at 14:30 in EOW 430 SPEAKER: Eugene Hyun TITLE: Location Aware Computing ABSTRACT: Location aware computing consists of the use of location information to improve the value of a wireless network for the users. Current technologies will be discussed as well as our novel approach; To use the power received signal strength (RSS) from Wireless Local Area Networks (WLAN) base stations. We implement a non-parametric kernel function to estimate the terminal's location. A presentation of our experimental setup and results will be presented. TIME/PLACE: Friday September 14 at 14:30 in EOW 430 SPEAKER: Parameswaran Ramachandran TITLE: Recent Research Progress Related to the Location of Hot Spots in Proteins Using Digital Filters ABSTRACT: Accurate and efficient location of hot spots in proteins is of prime importance in order to understand protein function. In an earlier work, we proposed and demonstrated a hot-spot location technique using a narrowband bandpass inverse-Chebyshev digital filter. In this talk, we present a preview of a new optimization-based filter design technique that can be used to design better digital filters capable of yielding more accurate hot-spot locations. We demonstrate the technique using several example protein sequences. TIME/PLACE: Friday March 16 at 14:30 in EOW 430 SPEAKER: Deepali Arora TITLE: Overview of Wireless Communications and Standards ABSTRACT: Wireless communications is a rapidly growing segment of the communications industry, with the potential to provide high-speed high-quality information exchange between portable devices located anywhere in the world. Potential applications enabled by this technology include multimedia Internet-enabled cell phones, video teleconferencing and distance learning, to name just a few. However, supporting these applications using wireless techniques poses significant technical challenges. This talk presents a brief overview of existing and emerging wireless technologies and standards. Some of the topics that will be discussed include different multiple access techniques, channel fading and techniques to combat the effects of fading and interference on system performance. A brief overview of cross-layer systems will also be discussed. Finally, some of the applications of TDMA and CDMA systems in current wireless systems will also be discussed in brief. TIME/PLACE: Thursday March 29 at 15:45 in EOW 430 SPEAKER: Mathieu Lagrange TITLE: Sound Source Tracking and Formation using the Normalized Cuts ABSTRACT: The goal of computational auditory scene analysis (CASA) is to create computer systems that can take as input a mixture of sounds and form packages of acoustic evidence such that each package most likely has arisen from a single sound source. We formulate sound source tracking and formation as a graph partitioning problem and solve it using the normalized cut which is a global criterion for segmenting graphs that has been used in Computer Vision. We describe how this formulation can be used with sinusoidal modeling, a common technique for sound analysis, manipulation and synthesis. Several examples showing the potential of this approach and its scalability to the analysis of multimodal (Audio+Video) systems will be provided. TIME/PLACE: Friday April 13 at 14:30 in EOW 430 SPEAKER: Di Xu TITLE: An Improved Multiscale Normal-Mesh-Based Image Coder ABSTRACT: Three modifications to the normal-mesh-based image coder of Jansen, Baraniuk, and Lavu are proposed, namely, the use of a data-dependent base mesh, an alternative representation for normal/vertical offsets, and a different scan-conversion scheme based on bicubic interpolation. Experimental results show that our proposed changes lead to improved coding performance in terms of both objective and subjective image quality measures. TIME/PLACE: Thursday April 26 at 15:45 in EOW 430 SPEAKER: Michael Adams TITLE: Triangulations and Signal Approximation ABSTRACT: Although regular (i.e., lattice-based) sampling is ubiquitous in signal processing, such sampling is usually highly suboptimal. Due to the nonstationary behavior of signals, irregular sampling often facilitates better signal approximations. In this talk, the speaker will introduce triangulations and explain how they can be employed in this context for representing signals defined on planar domains (such as images). The application of image approximation will be considered. TIME/PLACE: Thursday May 10 at 15:45 in EOW 430 SPEAKER: Pan Agathoklis TITLE: A Feature-based Algorithm for Image Registration ABSTRACT: In this talk an algorithm for aerial image registration will be presented. The objective of this algorithm is to register aerial images having only partial overlap, which are also geometrically distorted due to the different sensing conditions and in addition they may be contaminated with noise, may be blurred, etc. The geometric distortions considered in the registration process are rotation, translation and scaling. The proposed algorithm consists of three main steps: feature point extraction using a feature point extractor based on scale-interaction of Mexican-hat wavelets, obtaining the correspondence between the feature points of the firstt (reference) and the second image based on Zernike moments of neighborhoods centered on the feature points, and estimating the transformation parameters between the first and the second images using an iterative weighted least squares algorithm. Experimental results illustrate the accuracy of image registration for images with partial overlap in the presence of additional image distortions, such as noise contamination and image blurring. TIME/PLACE: Friday June 8 at 14:30 in EOW 430 SPEAKER: Ze Dong TITLE: Photography as a Hobby ABSTRACT: This presentation is not about research, but introduces photography as a hobby. The talk gives a brief overview of development of photography, and then focuses on the digital photography. Basic terminology and techniques in photography will be explained. The criterions judging the quality of pictures are discussed by way of sample images. TIME/PLACE: Friday June 22 at 14:30 in EOW 430 SPEAKER: Wu-Sheng Lu TITLE: Variational Methods for Image Processing: Part I ABSTRACT: In the conventional numerical optimization setting for an engineering analysis or design problem, the number of parameters to be optimized must be finite. On the other hand, images are two-variable functions and important image features such as edges and object contours are implicitly defined one-variable functions, and processing of images and image sequences such as de-noising, de-blurring, segmentation, etc. involve selection of best candidate images with noise and blurring effects removed and best contours highlighting objects of interest. Naturally, the "design parameters" in an effective optimization formulation for such image processing tasks are functions rather than finite-dimensional vectors. The mathematical foundation of such optimization formulation and solution methods is the calculus of variations (CoV), and the optimization techniques based on CoV are generally referred to as variational methods. In this talk, we give a brief overview of several successful variational methods developed in the 1990s and some recent research activities in the field. TIME/PLACE: Friday July 20 at 14:30 in EOW 430 SPEAKER: Wu-Sheng Lu TITLE: Variational Methods for Image Processing: Part II ABSTRACT: [This is a continuation of the speaker's earlier recent talk.] In Part II of the talk we shall cover two topics. We start with a quick review of the anisotropic diffusion method by Perona and Malik (PM) and present one of the many developments following the PM model, which was proposed by Catte, Lions, Morel and Coll in 1992 and has since attracted considerable attention. Next, we describe an active contour model proposed by Chan and Vese in 2001 for segmentation. The Chan-Vese model is based on the level set method originated from the work of Osher and Sethian on analyzing and computing moving fronts and minimization of the Mumford-Shah functional. We use examples to illustrate several key theoretical elements of the model and demonstrate the effectiveness of the model for image segmentation. TIME/PLACE: Friday August 3 at 14:30 in EOW 430 SPEAKER: Peter Hampton TITLE: Phase Correction Distribution Methods for a Woofer-Tweeter System of Deformable Mirrors ABSTRACT: In this talk I will introduce the Woofer-Tweeter test bench. A deformable mirror is an array of actuators that can bend a reflective surface. Similarly to audio aplications, the name Woofer refers to a low spatial and temporal frequency deformable mirror and the tweeter is a high spatial and temporal frequency deformable mirror. This system was used to prove a concept of using these two mirrors co-operatively to correct for distortions of star light. Fundamental concepts to classic adaptive optics will be presented. TIME/PLACE: Friday August 17 at 14:30 in EOW 430 [There are two presentations, each of which will take about 30 minutes.] *** PRESENTATION 1 *** SPEAKER: Arjuna Madanayake TITLE: FPGA Processors for Real-time 2D/3D IIR Frequency-planar/Beam Filters ABSTRACT: Broadband antenna arrays are finding increasing beam forming applications for ultra wideband (UWB) communications, radar imaging, radio astronomy, navigation and space research. Beam forming for antenna arrays is possible using various DSP algorithms based on finite impulse response (FIR) and infinite impulse response (IIR) filters. In this talk, we briefly review MDSP approaches to beam forming using first-order spatio-temporal 2D/3D IIR frequency-planar/beam digital plane-wave filters, and discuss our measurable progress towards single-chip real-time MDSP hardware implementations for eventual use with broadband smart antenna arrays. We discuss the design of novel distributed-parallel-processor (DPP) massively-parallel systolic-array hardware architectures that can potentially lead to 2D/3D real-time VLSI circuits for RF filtering at frame-rates of several GHz. We also report on intermediate frequency (<100MHz frame rate) field programmable gate array (FPGA) based prototypes of both 2D and 3D IIR DPP plane-wave filter circuits that we built and tested at the University of Calgary. *** PRESENTATION 2 *** SPEAKER: Thushara Gunaratne TITLE: Beamforming of Temporally-Broadband-Bandpass Plane Waves using 2D FIR Trapezoidal Filters ABSTRACT: Beamforming is an important array processing application that has been successfully used to selectively enhance desired spatio-temporal (ST) plane waves (PWs) according to their directions of arrival (DOAs) to recover the associated 1D temporal intensity functions, alleviating both co-channel interference, caused by other propagating ST signals, and non-propagating broadband noise. In this lecture, we present two new discrete-domain methods proposed for the beamforming of temporally broadband bandpass ST PWs using 2D FIR filters with novel trapezoidal-shaped passbands. The first method employs a complex-coefficient 2D FIR filter having an asymmetric trapezoidal-shaped passband at baseband and achieves the minimum possible temporal sampling rate for a given temporal bandwidth. The second method employs a real-coefficient polyphase 2D FIR filter having a rectangularly-symmetric double-trapezoidal-shaped passband and requires 50% less computational complexity for the same temporal bandwidth. Experimental results have confirmed that both methods are equally capable of enhancing the desired temporally broadband bandpass ST PWs according to their DOAs under severe co-channel interference and multipath fading. TIME/PLACE: Thursday August 30 at 15:45 in EOW 430 SPEAKER: Michael McGuire TITLE: An Analysis of Faster-Than-Nyquist Signalling ABSTRACT: In 1975, J.E. Mazo demonstrated that it is possible to increase the data rate of a digital communications system operating using 4-QPSK modulation over an additive white Gaussian noise (AWGN) channel by increasing the rate of the data pulses above the standard Nyquist criteria limit without increasing the bit error rate or required transmission bandwidth. This so-called Faster-than-Nyquist (FTN) signalling has not been used in real communications systems since the previously proposed implementation schemes require large amounts of computation in the receivers. This paper introduces a reformulation of FTN signalling in terms of a non-rectangular matrix multiplied by a sample vector of modulated 4-QPSK symbols. With this formulation, the receiver computing cost to detect the transmitted data for an AWGN channel is well within the complexity bounds for standard digital communication systems. This formulation enables an analysis of FTN signalling so that it may be directly compared to standard higher order modulation and data coding techniques. This presentation compares the attributes of FTN signalling in terms of required bandwidth, mean power, peak to average power ratio, and implementation complexity to other signalling schemes. Bounds on the performance gains for more general and higher dimensional FTN signalling schemes are also presented. TIME/PLACE: Thursday September 27 at 15:45 in EOW 430 SPEAKER: Ana Maria Sevcenco TITLE: Edge detection techniques in image processing ABSTRACT: Edge detection is the process which identifies the sharp changes of magnitude intensity in an image. A less strict definition is that edge detection identifies the "meaningful" discontinuities in intensity values of an image. Either way, the edge detection process can be regarded as one of the basic operations in image segmentation, image analysis, image recognition, image enhancement, image compression, or other image processing fields. There are many ways to perform edge detection such as first or second order derivative methods, wavelet techniques, or more recent algorithms as active contours. In this talk we briefly present the Canny edge detector, as a point-based oriented method using the gradient information of the image, the multi-scale edge detection using the wavelet transform, and the active contours algorithm, as a function-based oriented method in which an evolving curve, subject to constraints from a given image, detects the objects in that image. TIME/PLACE: Friday October 12 at 14:30 in EOW 430 SPEAKER: Yihai Zhang TITLE: Low Complexity Joint Semiblind Detection for OFDM Systems over Time-Varying Channels ABSTRACT: Orthogonal frequency division multiplexing (OFDM) modulation is widely used in communication systems to meet the demand for ever increasing data rates. However, it is sensitive to Doppler spread caused by user mobility, which results in intercarrier interference (ICI). In the design of most ICI reduction algorithms for OFDM systems, perfect channel information is assumed at the receiver. Many channel estimation methods have been proposed for OFDM systems based on pilot symbols. In most cases, channel estimation with pilot symbols is a robust method. However, there are disadvantages such as bandwidth loss and overhead, which can be excessive in fast fading channels. This motivates the use of joint blind or semiblind detection methods for OFDM systems. In this talk, a low complexity joint semiblind detection algorithm for OFDM systems over time-varying channels is presented based on the channel correlation and noise variance. Results are given which demonstrate that the proposed algorithm provides comparable performance with lower computational complexity than that of a sphere decoder. TIME/PLACE: Thursday October 25 at 15:45 in EOW 430 SPEAKER: Deepali Arora TITLE: The hidden beam problem in wireless communication systems ABSTRACT: The use of IEEE 802.11 wireless LAN systems (WLANs) over the last few years has increased tremendously and WLANs are no longer limited to homes and offices. The advancements in antenna technology and there use in WLANs has shown that the directional antennas are preferable over omni-directional antennas not only in terms of increased range, better directivity and substantial reduction in interference but also in large power savings which is a critical issue in wireless systems. To exploit the benefits offered by the directional antennas, several researchers have re-designed multiple access control (MAC) protocols by replacing omni-directional antennas with directional antennas. However, when used in IEEE 802.11 systems, directional antennas present their own share of issues such as the hidden node problem, the hidden beam problem and deafness. While some of these issues such as the hidden node problem and deafness have been widely investigated, the hidden beam problem has remained largely unaddressed. In this presentation an overview of the hidden beam problem and its effect on systems relying on carrier sensing is presented. Some of the earlier work done to solve the hidden beam problem will also be discussed in brief and a new technique and some initial results will be presented.