A Neural Network (NN) using Normalised Radial Basis Functions (NRBF) is used for encoding the sequence of positions forming the path of an autonomous wheelchair. The network operates by continuously producing the next position for the wheelchair. As the path passes several times over the same point, additional phase information is added to the position information. This avoids the aliasing problem. The use of normalised RBFs creates an attraction field over the whole space and enables the wheelchair to recover from perturbations, e.g. due to the avoidance of people.

Abstract-This paper main ly emphasizes on the POV (Persistence Of Vis ion) technology. In current era in which energy is the main factor in designing all the applications, maximu m and efficient use of the energy is very important. A POV d isplay has many advantages over a trad itional CRT, LCD or LED display, like power savings, less complexity, easy configuration, attractiveness etc. To overcome the drawback of o ld processor we have decided to implement the same display atop a new and advanced microprocessor, the Arduino duemilanove. This platform brings with it newer coding and a different understanding of peripherals. A RDUINO INTERFA CE BOARDS provide us with a low-cost, easy-to use technology to create the project. We also aim to build the newer display to work with modern forms of interfaces. To accomplish this, we will be interfacing the display with an Android device. This project can be implemented with help of any Android Smartphone/tablet running Android 4.0+.

No abstract

No abstract

Flicker is the most common and an intolerable blemish present in signal processing world that leads to distortion in the transmitted frame of a video string. To dodge such misinterpretations a technique for detection of the flickering frame in a video is depicted in this research. Earlier methods were based on removing flicker by calculating the threshold of the consecutive frame difference and then finding the flickering frame. The proposed method in this research includes finding flickering frame using neural network concept. Therefore, the advantage of the practice disclosed here is that it removes the tedious calculation part of the threshold value and thereby the computational part becomes easier with added accurate result.