Sharif Digital Repository

In a typical surveillance radar, decision about the existence of a target in certain range-azimuth-elevation cell is made from the echo received in current scan, while still there is useful information in history of that range cell that is not considered in decision making. Based on the potential of the Hough Transform to use history of both range and Doppler information, a new method to increase the probability of detection in surveillance radars is proposed. The new method uses a 3D data space and a special projection to detect targets and extract range, speed, and acceleration of maneuvering targets simultaneously  

In this paper, the problem of matrix rank minimization under affine constraints is addressed. The state-of-the-art algorithms can recover matrices with a rank much less than what is sufficient for the uniqueness of the solution of this optimization problem. We propose an algorithm based on a smooth approximation of the rank function, which practically improves recovery limits on the rank of the solution. This approximation leads to a non-convex program; thus, to avoid getting trapped in local solutions, we use the following scheme. Initially, a rough approximation of the rank function subject to the affine constraints is optimized. As the algorithm proceeds, finer approximations of the rank... 

Suppose that a solution x to an underdetermined linear system b=Ax is given. x is approximately sparse meaning that it has a few large components compared to other small entries. However, the total number of nonzero components of x is large enough to violate any condition for the uniqueness of the sparsest solution. On the other hand, if only the dominant components are considered, then it will satisfy the uniqueness conditions. One intuitively expects that x should not be far from the true sparse solution x0. It was already shown that this intuition is the case by providing upper bounds on ||x-x0|| which are functions of the magnitudes of small components of x but independent from x0. In... 

Inherent properties of UWB signals prevent both coherent and noncoherent processing with conventional methods used in narrow-band RADARs. In this paper, we show how to exploit the Hough transform, first developed to detect lines in an image distorted by noise, to detect moving objects from successive scans that are corrupted by noise and clutter. We discuss why conventional methods fail to process UWB pulses noncoherently/coherently and investigate different aspects of using the Hough transform in noncoherent integration of UWB signals. Simulation results to support our approach are also presented. © 2008 EuMA  

In this paper, based on a successively accuracy-increasing approximation of the ℓ0 norm, we propose a new algorithm for recovery of sparse vectors from underdetermined measurements. The approximations are realized with a certain class of concave functions that aggressively induce sparsity and their closeness to the ℓ0 norm can be controlled. We prove that the series of the approximations asymptotically coincides with the ℓ1 and ℓ0 norms when the approximation accuracy changes from the worst fitting to the best fitting. When measurements are noise-free, an optimization scheme is proposed that leads to a number of weighted ℓ1 minimization programs, whereas, in the presence of noise, we propose... 

Ambient Intelligence is a new paradigm in information technology that creates environments able to detect and respond to users’ needs, actions, behaviors and feelings. User trust plays an important role in accepting Ambient Intelligence environments. In this paper we describe the design and implementation of a virtual reality based testbed for studying trust in Ambient Intelligence Environments  

A multiplexing technique, which is based on duty-cycle division, is proposed. The channel multiplexing and demultiplexing are performed electrically at the single user bit rate, which is very economic. In a three-user system (3×10 Gb/s), the simulation results show that the best receiver sensitivity value achieved is -30.1 dBm with an optical signal-to-noise ratio (OSNR) of 22.3 dB, while the chromatic dispersion tolerance ranges from 192 to 280 ps/nm. Migration from 30 to 120 Gb/s is achieved with the penalty of 6.4 and 5.2 dB in the receiver sensitivity and OSNR, respectively, for the worst user  

Electrodeposition/dissolution of cadmium onto a film of mercury shows some deviations from the natural liquidity of mercury caused by the reduction of Cd onto it. Percolation and fractal analyzes were done on the surface and the bulk of the mercury film during diffusion of Cd species (atoms). These show that the fractal dimensions of the Cd-inserted mercury film are about 2.11 and 2.54 near the surface of the mercury film and at deeper points inside the film, respectively. The insertion process has a negligible effect on the surface morphology of the mercury film and there is a phase transition in the bulk, as well as a geometrical transition during the Cd-insertion (de-insertion) process.... 

This paper addresses an adaptive observer-based control for a switched fractional-order uncertain nonlinear system subject to input nonlinearities and asymmetric output constraints. The switching signal is arbitrary, and the designed controller needs no information regarding this signal. By employing a universal framework, the designed controller can cope with different input nonlinearities in different modes without having any information about their characteristics. It is assumed that only system output is measured, and a designed observer estimates the system states for control implementation. The uncertainties are approximated by intelligent approximators like fuzzy logic systems (FLS)... 

The belief propagation algorithm is a state of the art decoding technique for a variety of linear codes such as LDPC codes. The iterative structure of this algorithm is reminiscent of a neural network with multiple layers. Indeed, this similarity has been recently exploited to improve the decoding performance by tuning the weights of the equivalent neural network. In this paper, we introduce a new network architecture by increasing the number of variable-node layers, while keeping the check-node layers unchanged. The changes are applied in a manner that the decoding performance of the network becomes independent of the transmitted codeword; hence, a training stage with only the all-zero...