Implementation Of Filtering Algorithms Research Articles

Software Filtering Applications for the Analysis of Dental Images

Even if digital radiography is performed using modern procedures, which allow viewing and enlarging the image on the computer monitor, sometimes, due to the distortions introduced by the equipment or the need to perform a thorough analysis with a high degree of precision, image processing is required. For this matter, in this paper we present a software application created to help the dental practitioners, when they need a clear image, to discover the dental diseases or other submicroscopic problems on the dental surface, in the incipient phase, bone loss or any other problems that cannot be seen from a medical image, mainly due to the distortions introduced by the equipment. The advantages of dental image processing consist of brightness adjustment (attenuation, accentuation), contrast adjustment (attenuation, accentuation), image negation, histogram equalization, color transformation or noise removal. The paper describes the software accomplishment and implementation of filtering algorithms, which are efficient compared to the existing solutions, which can be used to improve the quality of the medical imaging. The algorithms, implemented in Java, are obtained by modifying the operators and procedures of the fundamental algorithms

Digital Filter Application for Squelch on Industrial Frequency Noise and its Harmonic Waves Interference

Industrial frequency and its harmonious waves are one of the main interferences in electronic measurement, which will cause severe influence on test accuracy. Digital filter is better than analog filter at resolution; furthermore multi-band stop digital filter design is unrealizable for analog filter design method. This paper designs an FIR(Finite Impulse Response) multi-band stop digital filter to reject the noise of 50 Hz and its harmonic waves from power network, whose stop bands are respectively as 48~52 Hz, 98~102 Hz and 148~152 Hz. Simulation results prove that the noise can be depressed to 30 dB. To analyze the filtered signal can improve accuracy of the test system. The whole course includes two parts, which are filter mathematical modeling and filter algorithm implementation on worksite data.

Application of inverse problem algorithms for integrated circuit temperature estimation

This article presents an approach to the application of inverse problem algorithms for integrated circuit temperature estimation. In order to estimate circuit temperature from remote sensor measurements, it is necessary to solve an inverse heat conduction problem (IHCP). As the IHCPs are extremely sensitive to input data errors, special algorithms must be used to obtain robust estimates of circuit temperature. Computer simulations have been performed applying different algorithms to produce circuit temperature estimates in case of multiple heat sources. Simulation results are presented. Additionally, the possibility of digital filter algorithm implementation is discussed.

Implementation of Kalman and adaptive Kalman filtering algorithms for digital distance protection on a vector signal processor

Implementation of two Kalman filtering processes for use in digital distance protection schemes is discussed. The first method uses Kalman filtering to determine the type of fault and fault location, while the second method utilizes adaptive Kalman filtering and conditional probabilities. Both techniques can be divided into five major components: fault detection, postfault current and voltage estimation (filtering), fault classification, zone computation, and fault location. This research focuses on the implementation of the filtering algorithms on the Zoran ZR34161 vector signal processor. The algorithm was tested on the Zoran vector signal processor simulator. The results are presented and discussed. >