Sharif Digital Repository

The current statistical model and adaptive filtering (CSMAF) algorithm is one of the most effective methods for tracking the maneuvering targets. However, it is still worthy to investigate the characteristics of the CSMAF algorithm, which has a higher precision in tracking the maneuvering targets with larger accelerations while it has a lower precision in tracking the maneuvering targets with smaller acceleration. In this paper a novel adaptive tracking algorithm for maneuvering targets is proposed. To overcome the disadvantage of the CSMAF algorithm, a simple multi-layer feedforward neural network (NN) is used By introducing NN, two sources of information of the filter are fused while its... 

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... 

According to the fact that humans and animals show marvelous abilities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground and it can easily rotate about the toe or the heel, the problem of controlling the biped robots is difficult. In this paper, according to the adaptive locomotion patterns of animals, coordination and control of body links have been done with Central Pattern Generator (CPG) in spinal cord and feedback network from musculoskeletal system. A one layer feedforward neural network that its inputs are the scaled joint variables and the touch sensors... 

Equivariant adaptive separation via independence (EASI) is one of the most successful algorithms for blind source separation (BSS). However, the user has to choose non-linearities, and usually simple (but non-optimal) cubic polynomials are applied. In this paper, the optimal choice of these non-linearities is addressed. We show that this optimal non-linearity is the output score function difference (SFD). Contrary to simple non-linearities usually used in EASI (such as cubic polynomials), the optimal choice is neither component-wise nor fixed: it is a multivariate function which depends on the output distributions. Finally, we derive three adaptive algorithms for estimating the SFD and... 

In this paper, a target parameter estimation problem is addressed for the recently emerging frequency diverse array multiple-input multiple-output (FDA-MIMO) radar system, utilizing sparse learning. The scene is modeled as a two dimensional (2D) angle-incremental range grid. To solve the resulting sparse problem, the recently proposed user-parameter free algorithms including block sparse learning via iterative minimization (BSLIM), iterative adaptive approach (IAA), sparse iterative covariance-based estimation (SPICE), likelihood-based estimation of sparse parameters (LIKES), and orthogonal matching pursuit (OMP) are applied which achieve excellent parameter estimation performance. However,... 

Incorporating the finite-element method for the modeling of the SQUID NDE response to a predefined defect pattern, an adaptive algorithm has been developed for the reconstruction of unknown defects using an optimization algorithm for updating of the forward problem. The defect reconstruction algorithm starts with an initial estimation for the defect pattern. Then the forward problem is solved and the obtained field pattern is compared with the measured signal from the SQUID NDE system. The result is used by an optimization algorithm to update the defect structure to be incorporated in the FEM forward problem for the next iteration. Since the mentioned model based inverse algorithm normally... 

It has been recently shown that guided modes in two-dimensional photonic crystal based structures can be fast and efficiently extracted by using the Galerkin's method with Hermite-Gauss basis functions. Although quite efficient and reliable for photonic crystal line defect waveguides, difficulties are likely to arise for more complicated geometries, e.g., for coupled resonator optical waveguides. First, unwanted numerical instability may well occur if a large number of basis functions are retained in the calculation. Second, the method could have a slow convergence rate with respect to the truncation order of the electromagnetic field expansion. Third, spurious solutions are not unlikely to... 

Nonlinearity characteristics, such as backlash, in various mechanisms, limit the performance of feedback systems by causing delays, undesired oscillations and inaccuracy. Backlash influence analysis and modeling is necessary to design a precision controller for this nonlinearity. Backlash between meshing gears in an electromechanical system is modeled by the use of differential equations and a nonlinear spring-damper. According to this model, the paper shows that oscillations and delays cannot be compensated by a state feedback controller. Therefore, an adaptive algorithm is designed, based on different regions of the system angular position error. Since this controller needs an estimation... 

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... 

According to the fact that humans and animals show marvelous capacities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground, the problem of controlling the biped robots is difficult. In other words, the biped walkers have fewer actuators than the degrees of freedom. So they are underactuated mechanical systems. In this paper according to the humans and animals locomotion algorithms, the stability of an underactuated biped walker having point feet is investigated by central pattern generators. For tuning the parameters of the CPG, an effective energy based...