Determination of Good and Bad Signal in a Given Random Signals Using MATLAB

In this modern world we are surrounded by all kinds of signals in various forms. Some of the signals are natural, but most of the signals are manmade. Some signals are necessary (speech), some are pleasant (music), while many are unwanted or unnecessary in a given situation. Therefore extracting or enhancing the useful information from a mix of conflicting information is the simplest form of signal processing [1]. Signal processing is so wide and very interesting in solving many engineering problems, in this paper we used it in bad and good signal detection where by the different samples of signals (sound wave) were provided and from there to select the good ones or bad ones using MATLAB software with the help of Fast Fourier Transform (FFT). Signal analysis procedures have been followed to get the required results by comparing the good known signal s1 and the rest of unknown random signals s2 and s3. Most parameters used in comparison are cross correlation factor and the magnitude of the given signal samples. In the final part we will be able to see the resulting waves using MATLAB showing both magnitude and cross correlation

Design of Dual -Band Coax Patch Antenna for GSM and Bluetooth Applications

This paper proposes the design of dual-band coax patch antenna for GSM and Bluetooth applications. The proposed antenna is suggested to be used in a mobile phone handset that covers dual frequency bands which include GSM1900(1850-1990MHz) and Bluetooth(2400-2483.5MHz).The simulation of the antenna is performed using a High Frequency Structure Simulator(HFSS) software. Analysis for return loss, VSWR, gain and radiation pattern were carried out. The proposed antenna shows return loss of -29dB at 1.9GHz and -30dB at 2.4GHz which implies good results. The impedance matching is good at the desired frequencies with VSWR < 2 respectively. The overall simulation results shows that the antenna worked well at the desired dual frequencies and hence making the antenna suitable for use in both GSM and Bluetooth applications. This antenna is implemented on FR4 Epoxy dielectric substrate with relative permittivity

Noise Reduction Using Arithmetic Mean Filtering (A Comparison Study of Application to Different Noise Types)

Images are often corrupted by unwanted signals otherwise known as noise during acquisition and transmission alike, leading to loss of clarity of information in severe cases. Image restoration aimed at reduction in degradation and noise removal thus becomes imperative in digital image processing. This work focuses on the restoration of corrupted images in the presence of noise only. The arithmetic mean filter was applied to denoise an image sample corrupted by different noise types and its performance on the noise types was compared using the average percentage difference in the pixel values of the original and denoised image as well as the Peak-signal-to-noise ratio (PSNR). Simulation results show that the Arithmetic Mean Filter performs best on the image corrupted by Poisson Noise

Optimetric analysis of 1x4 array of circular microwave patch antennas for mammographic applications using adaptive gradient descent algorithm

Interest in the use of microwave equipment for breast imagery is on the increase owing to its safety, ease of use and friendlier cost. However, some of the pertinent blights of the design and optimization of microwave antenna include intensive consumption of computing resources, high price of software acquisition and very large optimization time. This paper therefore attempts to address these concerns by devising a rapid means of designing and optimizing the performance of a 1×4 array of circular microwave patch antenna for breast imagery applications by deploying the adaptive gradient descent algorithm (AGDA) for a circumspectly designed artificial neural network. In order to cross validate the findings of this work, the results obtained using the adaptive gradient descent algorithm was compared with those obtained with the deployment of the much reported Levenberg-Marquardt algorithm for the same dataset over same frequency range and training constraints. Analysis of the performance of the AGDA neural network shows that the approach is a viable and accurate technique for rapid design and analysis of arrays of circular microwave patch antenna for breast imaging

Optimetric analysis of 1x4 array of circular microwave patch antennas for mammographic applications using adaptive gradient descent algorithm

Interest in the use of microwave equipment for breast imagery is on the increase owing to its safety, ease of use and friendlier cost. However, some of the pertinent blights of the design and optimization of microwave antenna include intensive consumption of computing resources, high price of software acquisition and very large optimization time. This paper therefore attempts to address these concerns by devising a rapid means of designing and optimizing the performance of a 1×4 array of circular microwave patch antenna for breast imagery applications by deploying the adaptive gradient descent algorithm (AGDA) for a circumspectly designed artificial neural network. In order to cross validate the findings of this work, the results obtained using the adaptive gradient descent algorithm was compared with those obtained with the deployment of the much reported Levenberg-Marquardt algorithm for the same dataset over same frequency range and training constraints. Analysis of the performance of the AGDA neural network shows that the approach is a viable and accurate technique for rapid design and analysis of arrays of circular microwave patch antenna for breast imaging

DEVELOPMENT OF AN ARDUINO-BASED OBSTACLE AVOIDANCE ROBOTIC SYSTEM FOR AN UNMANNED VEHICLE

The use of autonomous systems in the world to perform relevant and delicate task is fast growing. However, its application in various fields cannot be over emphasized. This paper presents an obstacle detection and avoidance system for an unmanned Lawnmower. The system consists of two (Infrared and Ultrasonic) sensors, an Arduino microcontroller and a gear DC motor. The ultrasonic and infrared sensors are implemented to detect obstacles on the robot’s path by sending signals to an interfaced microcontroller. The micro-controller redirects the robot to move in an alternate direction by actuating the motorsin order to avoid the detected obstacle. The performance evaluation of the system indicates an accuracy of 85% and 0.15 probability of failure respectively. In conclusion, an obstacle detection circuit was successfully implemented using infrared and ultrasonic sensors modules which were placed at the front of the robot to throw both light and sound waves at any obstacle and when a reflection is received, a low output is sent to the Arduino microcontroller which interprets the output and makes the robot to stop

RESOURCEFUL SELECTION-BASED DESIGN OF WIRELESS UNITS FOR GRANARY MONITORING SYSTEMS

The effectiveness of any granary system is grossly dependent up on the efficiency of its monitoring and control measures. The granary monitoring systems presently in use in mo st developing countries are based on wired networks with inevitable disadvantages that include high installation and mai ntenance costs. Most wireless granary monitoring systems previously developed were achieved without resort to resourcefu lness of the composite units of the system. However, record information on the selection of best comparative compone nts for wireless granary monitoring systems is not readily available. This paper designed a wireless sensor integrated sys tem from comparison and selection of resourceful component units for monitoring temperature, humidity and light variations in stored bulk grains. The resulting composite units of the developed system were products of the best paramet ers trade-off in the selection of components and protocols. The sensing unit consists of the selected Grove-DHT22 Temperatu re/Humidity sensor with calibrated, linearized and stable digital signals output via 1-wire bus and a cheap low-power Gro ve-GL5528 light sensor. The resulting network had no hierarchy or parent-child relationship constraint. The low-powe r sleep configuration possibility of the sensor node was cyclic and synchronize

Noise Measurement, Characterization, and Modeling for Broadband Indoor Power Communication System: A Comprehensive Survey

A thorough study of the literature suggests that greater attention has to be paid to power line noise measurements, characterization, and modeling. Several studies show that significant differences do exist, and the findings are somewhat conflicting. This may be attributed to the diverse environment under investigation, which includes volatile noise sources, differences in electrical grid structure from country to country, topology, and unknown power cable characteristics. An in-depth analysis of the approaches for measuring, characterizing, and modeling noise, as well as the descriptions of relevant components, and the environment needed to carry out the measurements, is presented. This review serves as a roadmap for academics and engineers in the deployment of power line communication systems