Sharif Digital Repository

In this paper, we present a novel multilinear algebra based feature extraction approach for face recognition which preserves some implicit structural or locally-spatial information among elements of the original images. We call this method three-dimensional modular discriminant analysis (3DMDA). Our approach uses a new data model called third-order tensor model (3TM) for representing the face images. In this model, each image is partitioned into the several equal size local blocks, and the local blocks are combined to represent the image as a third-order tensor. Then, a new optimization algorithm called direct mode (d-mode) is introduced for learning three optimal projection axes. Extensive... 

One limitation of vector-based LDA and its matrix-based extension is that they cannot deal with heteroscedastic data. In this paper, we present a novel two-dimensional feature extraction technique for face recognition which is capable of handling the heteroscedastic data in the dataset. The technique is a general form of two-dimensional linear discriminant analysis. It generalizes the interclass scatter matrix of two-dimensional LDA by applying the Chernoff distance as a measure of separation of every pair of clusters with the same index in different classes. By employing the new distance, our method can capture the discriminatory information presented in the difference of covariance... 

Motivated by the fact that in computer vision data samples are matrices, in this paper, we propose a matrix-variate probabilistic model for canonical correlation analysis (CCA). Unlike probabilistic CCA which converts the image samples into the vectors, our method uses the original image matrices for data representation. We show that the maximum likelihood parameter estimation of the model leads to the two-dimensional canonical correlation directions. This model helps for better understanding of two-dimensional Canonical Correlation Analysis (2DCCA), and for further extending the method into more complex probabilistic model. In addition, we show that two-dimensional Linear Discriminant... 

There is a growing attention in subspace learning using tensor-based approaches in high dimensional spaces. In this paper we first indicate that these methods suffer from the Heteroscedastic problem and then propose a new approach called Heteroscedastic Multilinear Discriminant Analysis (HMDA). Our method can solve this problem by utilizing the pairwise chernoff distance between every pair of clusters with the same index in different classes. We also show that our method is a general form of Multilinear Discriminant Analysis (MDA) approach. Experimental results on CMU-PIE, AR and AT&T face databases demonstrate that the proposed method always perform better than MDA in term of classification... 

Automatic speech recognition performance degrades significantly when speech is affected by environmental noise. Nowadays, the major challenge is to achieve good robustness in adverse noisy conditions so that automatic speech recognizers can be used in real situations. Spectral subtraction (SS) is a well-known and effective approach; it was originally designed for improving the quality of speech signal judged by human listeners. SS techniques usually improve the quality and intelligibility of speech signal while speech recognition systems need compensation techniques to reduce mismatch between noisy speech features and clean trained acoustic model. Nevertheless, correlation can be expected... 

This paper has presented a novel discriminative parameters calibration approach based on the Model Distance Maximizing (MDM) to improve the performance of our previous proposed robustness method named spectral subtraction (SS) in likelihoodmaximizing framework. In the previous work, for adjusting the spectral over-subtraction factor of SS, conventional ML approach is used that only utilizes the true model without considering other confused models. This makes it very probably to reach a suboptimal solution. While in MDM, by maximizing the dissimilarities among models, the performance of our speech recognizer-based spectral subtraction method could be further improved. Experimental results... 

In this paper a novel method called Extended Two-Dimensional PCA (E2DPCA) is proposed which is an extension to the original 2DPCA. We state that the covariance matrix of 2DPCA is equivalent to the average of the main diagonal of the covariance matrix of PCA. This implies that 2DPCA eliminates some covariance information that can be useful for recognition. E2DPCA instead of just using the main diagonal considers a radius of r diagonals around it and expands the averaging so as to include the covariance information within those diagonals. The parameter r unifies PCA and 2DPCA. r=1 produces the covariance of 2DPCA, r=n that of PCA. Hence, by controlling r it is possible to control the... 

Spectral Subtraction (SS), as a speech enhancement technique, originally designed for improving quality of speech signal judged by human listeners. it usually improve the quality and intelligibility of speech signals, while the speech recognition systems need compensation techniques capable of reducing the mismatch between the noisy speech features and the clean models. This paper proposes a novel approach for solving this problem by considering the SS and the speech recognizer as two interconnected components, sharing the common goal of improved speech recognition accuracy. The experimental evaluations on a real recorded database and the TIMIT database show that the proposed method can... 

Side Channel Analysis (SCA) are still harmful threats against security of embedded systems. Due to the fact that every kind of SCA attack or countermeasure against it needs to be implemented before evaluation, a huge amount of time and cost of this process is paid for providing high resolution measurement tools, calibrating them and also implementation of proposed design on ASIC or target platform. In this paper, we have introduced a novel simulation platform for evaluation of power based SCA attacks and countermeasures. We have used Synopsys power analysis tools in order to simulate a processor and implement a successful Differential Power Analysis (DPA) attack on it. Then we focused on the... 

In this paper we present a novel approach for adjusting a multi band spectral subtraction filter coefficients based on speech recognition system results. Currently most speech enhancement techniques are designed according to various waveform level criteria such as maximizing SNR or minimizing signal error. However improvement in these criteria does not necessarily result in increasing speech recognition performance. Only if these methods generate sequence of features that maximize or increase the likelihood of the correct transcription relative to other incorrect competing hypotheses, speech recognition performance will increase. Here we use an utterance with a known transcription and... 

Channel distortion may dramatically degrade speech recognition performance in a distant environment. Authors in their recent work [1] proposed a novel spectral subtraction method which they named it maximum likelihood based spectral subtraction (MLBSS). They indicated that recognition performance could be improved dramatically by adjusting filter parameters based on recognition results. Previous results show effectiveness of this method in dealing with additive distortion. In this paper we propose an approach for increasing robustness of this method against channel distortion in distant talking environment. We add Cepstral Mean Normalization (CMN) in designing MLBSS filter and show that by... 

Using multiple antennas at the transmit and receive sides of a passive radar brings both the benefits of MIMO radar and passive radar. However one of the obstacles arisen in such configuration is the receive antennas placement in proper positions so that the radar performance is improved. Here we just consider the case of positioning one receiver among multiple illuminators of opportunity. Indeed it is a start for the solution of optimizing the geometry of the multiple receivers in a passive radar  

SbCl3 supported on montmorillonite K-10 is an efficient catalyst for the ring opening of epoxides with aromatic amines under solvent-free conditions and microwave irradiation to give the corresponding b-amino alcohols in high yields with high regioselectivity  

In this paper, we consider an integrated sensing and communication (ISAC) system with wireless power transfer (WPT) where an unmanned aerial vehicle (UAV)-based radar serves a group of energy-limited communication users in addition to its sensing functionality. In this architecture, the radar senses the environment in phase 1 (namely sensing phase) and mean-while, the communications users (nodes) harvest and store the energy from the radar transmit signal. The stored energy is then used for information transmission from the nodes to UAV in phase 2, i.e., uplink phase. Performance of the radar system depends on the transmit signal as well as the receive filter; the energy of the transmit... 

One of the important obstacles in MIMO (Multiple Input Multiple Output) radars is the issue of designing proper transmit signals. Indeed, the capability of signal design is a significant advantage in MIMO radars, through which, the system can achieve much better performance. Many different aspects of this performance improvement have been considered yet, and the transmit signals have been designed to attain such goal, e.g., getting higher SNR or better detector's performance at the receiver. However, an important tool for evaluating the radar's performance is its ambiguity function. In this paper, we consider the problem of transmit signal design, in order to optimize the ambiguity function... 

Two gains play key roles in recently developed MIMO wireless communication systems: "spatial diversity" gain and "spatial multiplexing" gain. The diversity gain refers to the capability to decrease the error rate of the MIMO channel, while the multiplexing gain implicitly refers to the amount of increase in the capacity of the MIMO channel. It has been shown that there is a fundamental tradeoff between these two types of gains, meaning interplay between increasing reliability (via an increase in the diversity gain) and increasing data rate (via an increase in the multiplexing gain). On the other hand, recently, MIMO radars have attracted much attention for their superior ability to enhance... 

It is a well known fact that using multiple antennas at transmit and receive sides improves the detection performance. However, in such multiple-input multiple-output (MIMO) configuration, proper positioning of transmitters and receivers is a big challenge that can have significant influence on the performance of the overall system. In addition, determining the power of each transmitter under a total power constraint is a problem that should be solved in order to enhance the performance and coverage of such a system. In this paper, we design the Neyman-Pearson detector under the Rayleigh scatter model and use it to introduce a criterion for the antenna placement at both transmit and receive... 

There has been much interest, recently, towards exploiting the Multiple-Input Multiple-Output (MIMO) technique in radar. It is shown that using multiple antennas at transmit and receive sides can improve the performance of the system. However, in order to analyze the system's performance, its ambiguity function, i.e. the ambiguity function of a MIMO radar, is needed to be defined. In this paper, beginning from the information theoretic definitions, we derive such function, specifically for a MIMO radar with widely separated antennas  

By combining the two ideas of MIMO (Multiple Input Multiple Output) and PCL (Passive Coherent Location) in radar, one can achieve the advantages of both recently developed techniques simultaneously. While using multiple antennas at the receive side provides a spatial diversity of the object to be detected, using multiple illuminators of opportunity, most importantly, makes the radar covert to the interceptors. One obstacle in such MIMO configuration is choosing the positions of the receive antennas. In this paper, after analyzing the Neyman-Pearson detector for the DVB-T based PCL, we introduce the probability of missed detection as a criterion to place the receive antenna. Here, we only...