Journal of Computer and Robotics
Volume:5 Issue: 2, Summer and Autumn 2012

Augmented Downhill Simplex Method (ADSM) is introduced here, that is a heuristic combination of Downhill Simplex Method (DSM) with Random Search algorithm. In fact, DSM is an interpretable nonlinear local optimization method. However, it is a local exploitation algorithm; so, it can be trapped in a local minimum. In contrast, random search is a global exploration, but less efficient. Here, random search is considered as a global exploration operator in combination with DSM as a local exploitation method. Thus, presented algorithm is a derivative-free, fast, simple and nonlinear optimization method that is easy to be implemented numerically. Efficiency and reliability of the presented algorithm are compared with several other optimization methods, namely traditional downhill simplex, random search and steepest descent. Simulations verify the merits of the proposed method.

In today’s competitive market, for a business firm to win higher profit among its rivals, it is of necessity to evaluate, and rank its potential customer segments to improve its Customer Relationship Management (CRM). This brings the importance of having more efficient decision making methods considering the current fast growing information era. These decisions usually involve several criteria, and it is often necessary to compromise among possibly conflicting factors. In this paper a new extension of fuzzy Techniques for Order Preferences by Similarity to Ideal Solution (TOPSIS) based on Shannon entropy concept for customer segment selection is proposed. Fuzzy set theories are also employed due to the presence of vagueness and imprecision of information. The contribution of this paper is that it provides a framework for MCDM which considers vagueness and ambiguity as well as allowing to set multiple aspiration levels for customer segment selection problems in which ‘‘the more/higher is better’’ (e.g., benefit criteria) or ‘‘the less/lower is better’’ (e.g., cost criteria).At the end, a numerical example of this approach is shown to illustrate its effectiveness.

This paper presents a new method to reduce consumption power in flash ADC in 65nm CMOS technology. This method indicates a considerable reduction in consumption power, by removing comparators memories. The simulations used a frequency of 1 GHZ, resulting in decreased consumption power by approximately 90% for different processing corners. In addition, in this paper the proposed method was designed using interpolation technique for purpose of promoting the performance as well as decreasing the class of chip. The simulation results indicate that the consumption power for interpolation technique was decreased by approximately 5% compared to the proposed method. Also, we compare the results of the proposed technique with those of convertors frequently referred in other studies. The results show that the consumption power is considerably decreased, using the proposed technique.

The goal of multi-frame Super Resolution (SR) is to fuse multiple Low Resolution (LR) images to produce one High Resolution (HR) image. The major challenge of classic SR approaches is accurate motion estimation between the frames. To handle this challenge, fuzzy motion estimation method has been proposed that replaces value of each pixel using the weighted averaging all its neighboring pixels in all LR images which carries the degree of similarity between image blocks centered on two pixels. Since in case of rotation between LR images, comparing the gray level of blocks around the pixels is not a suitable criterion for calculating weight, so, magnitude of Zernike Moments (ZM) has been used as a rotation invariant feature. Due to the lower sensitivity of Pseudo Zernike Moments (PZM) to noise and the higher discrimination capability of it for the same order compared to ZM, in this paper, we propose a new method based on magnitude of PZM of the blocks as a rotation invariant descriptor for representation of pixels in weight calculation. Experimental results on several image sequences show that the performance of the proposed algorithm is better than the existing and new techniques from the aspect of PSNR and visual image quality.

This paper investigates on control and stabilization of a new hyperchaotic system. The hyperchaotic system is stabilized using a new technique which called Generalized Backstepping Method (GBM). Because of its similarity to Backstepping approach, this method is called GBM. But, this method is more applicable in comparison with conventional Backstepping.  Backstepping method is used only for systems with strictly feedback form, but GBM works for a wide range form of the nonlinear dynamical systems. In Design procedure, two cases is considered that their difference is in the number of control inputs. Numerical simulation results are presented to show the effectiveness of the proposed controller.

As a robot could be stable statically standing on three or more legs, a six legged walking robot can be highly flexible in movements and perform different missions without dealing with serious kinematic and dynamic problems. An experimental six legged walking robot with 18 degrees of freedom is studied and built in this paper. The kinematic and gait analysis formulations are demonstrated by an experimental hexapod robot. The results show that the robot walks well as it was simulated.