Median filters are commonly used for removal of the impulse NOISE from images. De-noising is a preliminary step in online processing of images, thus hardware implementation of median filters is of great interest. Hence, many methods, mostly based on sorting the pixels, have been developed to implement median filters. Utilizing vast amount of hardware resources and not being fast are the two main disadvantages of these methods. In this paper a method for filtering images is proposed to reduce the needed hardware elements. A modular pipelined median filter unit is first modeled and then the designed module is used in a parallel structure. Since the image is applied in rows and in a parallel manner, the amount of necessary hardware elements is reduced in comparison with other hardware implementation methods. Also, image filtering speed has increased. Implementation results show that the proposed method has advantageous speed and efficiency.

Distributed estimation in communication networks is an issue that has received a lot of attention recently. One of the most challenging issues in these networks is the communication reduction of the network. Recently, researchers have proposed methods to reduce the communication load that while reducing the communication load in the network, have less impact on the final performance of the network. For signal processing in nonlinear space, correntropy has been regarded as an information criterion in recent years. Of course, in Gaussian space, the use of correntropy does not always work well, but if we have impulse NOISE, the cost function based on correntropy is better than the cost function based on square estimation error. In this research work, network NOISE is impulse NOISE. To have less destructive effect on the final performance of the network, a new solution is presented based on information criteria. Correntropy is a good criterion as a measure of similarity between two random variables that are in the same space and also because correntropy is not sensitive to sudden changes. Node deletion is performed intelligently and based on correntropy between the reference node and neighboring nodes. Also, a mathematical analysis shows that the condition of deletion of nodes is not dependent on the parameters of the correntropy kernel. The simulation results show that this method has less final MSD than other methods of reducing the network communication load.

Introduction: Impulse NOISE removal of mammography image is of great importance. The presence of different signs and characteristics of the disease has made it difficult for physicians’ to diagnose. MLP neural network allows the analysis of the patients’ medical data for medical decisions. The goal of this paper is to present an accurate model designed for reduction of degradation caused by high density IMPULSIVE NOISE in mammography images.Methods: In this study, the medical case files of 574 patients. Patient information was acquired from the Mortaz General Hospital Standard Database and selected. GBC Algorithm and MLP neural network are used for reduction of degradation Caused by high density IMPULSIVE NOISE in mammography images.Results: The suggested model was compared with the MDBUTMD and ATSM methods. In reduction of degradation caused by high density IMPULSIVE NOISE in mammography images, the suggested model acquired the least error and the most PSNR and validation in comparison with other methods. The ATSM method has the most error and least PSNR.Conclusion: Subjective and objective evaluations on different images with different NOISE densities show the superiority of the proposed method over the related recent works in the field.

Introduction: Cochlear dead zones are defined as areas where the inner hair cells have been destroyed.Thresholds on the audiograms show the integrity of those parts of the ear that are tested. Care must be taken in interpretating audiograms. Thanks to the advances in understanding of cochlear functions, it is now possible to spot false responses that come from dead zones of the cochlea. Recently, cochlear dead regions have been detected via TEN (Threshold Equalizing NOISE) test in which ipsilateral broadband NOISE and threshold shifting are used.Materials and Methods: A review of the literature on the subject of dead zones published from 1993 to 2003 was performed using Pubmed, Ebsco, Science Direct, Google Scholar Thieme ProQuest databases and library sources. key word: were "cochlear dead zone", "traveling wave", "ten (threshold equalizing NOISE) test", "ipsilateral NOISE" and "real-ear measurement for hearing aids prescription".Conclusion: Hearing aids fitting process for patients with severe and sloping sensory neural hearing loss must be noted specially by amplifying active zone and avoiding amplification for dead region i.e., offering amplification to the transition frequencies that have better hearing than others, those among the fine regions and the dead zones. Dead zone detection may help in hearing aids fitting and fine tuning.

In this paper, a new method for extending and relaxing the NOISE-coupling (NC) technique is proposed to enhance the NOISE-shaping order without adding the number of integrators. The NOISE-shaping order of the introduced ∑∆ modulator whit applying a second-order NOISE-coupling technique is enhanced and its performance with optimizing the NOISE transfer function (NTF) zeros is improved. Also, by removing the analog adder at feedforward path and transferring it to a new feedback branch before the last integrator and adding second-order NC path can be decreased the input voltage swing to the quantizer. Thus, by improving the modulator resolution, power consumption can be reduced. Mathematical analyses and behavioural simulation results confirm the effectiveness of the new NC method. To examine its performance, a 2nd-order single loop ΣΔ modulator was designed. The new NOISE-coupling method is used to achieve the three-order NOISE shaping to increase the resolution with low complexity and low-power. The results show an outstanding improvement in signal-to-NOISE and distortion ratio (SNDR) compared to the conventional structure.

This paper addresses the performance of MIMO-OFDM communication system in environments where the interfering NOISE exhibits non-Gaussian behavior due to IMPULSIVE phenomena. It presents the design and simulation of an iterative technique that aims to minimize the effect of IMPULSIVE NOISE on the performance of the MIMO-OFDM communication system under Additive White Gaussian NOISE (AWGN) channel. This is a new method to recover the signals corrupted by IMPULSIVE NOISE in MIMO-OFDM systems over In-home Power Line Channel. The location and amplitude IMPULSIVE NOISE at the receiver using an adaptive threshold to be determined. Reduced IMPULSIVE NOISE effects using the mask based on the soft decision method. By iteration, the original signal estimation can be used to improve the IMPULSIVE NOISE estimation. This continuous loop IMPULSIVE NOISE detection and mitigation a better estimate of the original signal is obtained. The Bit Error Rate (BER) performance of the MIMO-OFDM system in an IMPULSIVE NOISE environment was evaluated. The results show the superiority and robustness of the proposed method.