Sharif Digital Repository

To make a balance between time of detection and resolution of detection in radar, it must select an optimized time interval for integrations and signal bandwidth. In this paper, a new algorithm for finding best width of window and bandwidth of the FM signals for FM PCL radar is designed  

People usually use trust and reputation to cope with uncertainty which exists in the nature and routines. The existing approaches for inferring trust rely on homogeneous relations. In other words, trust is just inferred by a homogeneous relation. In this paper, we present a new model for inferring trust using heterogeneous social networks; we use relation extraction to make a trust relation from the other relation such as friendship and the college relation and then introduced an algorithm to infer trust using extracted relation. In order to get higher performance, we extend relation extraction problem by proposing a genetic algorithm. This algorithm is more scalable, interpretable and... 

In this paper, a new algorithm for Sparse Component Analysis (SCA) in the noisy underdetermined case (i.e., with more sources than sensors) is presented. The solution obtained by the proposed algorithm is compared to the minimum l1 -norm solution achieved by Linear Programming (LP). Simulation results show that the proposed algorithm is approximately 10 dB better than the LP method with respect to the quality of the estimated sources. It is due to optimality of our solution (in the MAP sense) for source recovery in noisy underdetermined sparse component analysis in the case of spiky model for sparse sources and Gaussian noise. © 2007 IEEE  

Optimal scheduling of runway operations plays an important role in improving safety and efficiency of any congested airspace. The objective of scheduling is runway assignment and computing arrival times that minimize delays and maximize runway throughput. Currently, methods for runway scheduling are categorized into First-Come-First-Serve (FCFS) and Constrained Position Shifting (CPS). In this work, we describe a new algorithm for real time scheduling for single as well as multiple parallel runway scheduling. The new approach is comparable to FCFS algorithms in accommodating practical issues while enjoying optimality similar to that of CPS methods. Different case studies show that the new... 

An stochastic version of the classical shortest path problem whereby for each node of a graph, a probability distribution over the set of successor nodes must be chosen so as to reach a certain destination node with minimum expected cost. In this paper, we propose a new algorithm based on Particle Swarm Optimization (PSO) for solving Stochastic Shortest Path Problem (SSPP). The comparison of our algorithm with other algorithms indicates that its performance is suitable even by the less number of iterations. © 2008 Springer-Verlag Berlin Heidelberg  

Genetic Algorithms are vastly used in development of rule based classifier systems in data mining. In such tasks, the rule base is usually a set of If-Then rules and the rules are developed using an evolutionary trait. GA is usually a good solution for such tasks as it globally searches for good rule-sets without any prior bias or greedy force, but it is usually slow. This paper presents a novel algorithm for rule base generation based on natural process of symbiogenesis. The algorithm uses symbiotic combination operator instead of traditional sexual recombination operator of genetic algorithms. The new algorithm is compared with genetic algorithm on some globally used benchmarks and it is... 

This paper presents a new algorithm for detecting user-selected objects in a sequence of images based on a new weighted adaptive lifting scheme transform. In our algorithm, we first select a set of coefficients as object features in the wavelet transform domain and then build an adaptive transform considering the selected features. The goal of the designed adaptive transform is to "vanish" the selected features as much as possible in the transform domain. After applying both non-adaptive and adaptive transforms to a given test image, the corresponding transform domain coefficients are compared for detecting the object of interest. We have verified our claim with experimental results on 1-D... 

In this paper, we present new adaptive linear discriminant analysis (LDA) algorithm and apply them for adaptive facial feature extraction. Adaptive nature of the proposed algorithm is advantageous for real world applications in which one confronts with a sequence of data such as online face recognition and mobile robotics. Application of the new algorithm on feature extraction from facial image sequences is given in three steps: i) adaptive image preprocessing, ii) adaptive dimension reduction and iii) adaptive LDA feature estimation. Steps 1 and 2 are done simultaneously and outputs of stage 2 are used as a sequence of inputs for stage3. The proposed system was tested on Yale and PIE face...