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  How to design simulation of PV with Boost converter in MATLAB Simulink Matlabhelpers demonstrate how to use the MATLAB software for simulation PV boost converter is a DC/DC power converter which steps up voltage from its input (source) to its output (load). In continuous conduction mode (current through the inductor never falls to zero), the theoretical transfer function of the boost converter is: Single Phase to 3phase Inverter Control The aim of the inverter is to export controllable power with the established voltage. The generated power is controlled by the in-phase current component which is proportional to the network power demand. The supervisory controller (SC), receiving power demand information from short-term/long-term prediction values, operates DG units either in a constant power output or in a load-following manner. the power set-points generate a current reference for the current regulator. The closed-loop controller ensures that the output current tracks the reference

  How to Noise removal from Noisy Audio signal using filters in MATLAB matlabhelpers demonstrate how to use the MATLAB software for simulation of Audio noise reduction system is the system that is used to remove the noise from the audio signals. Audio noise reduction systems can be divided into two basic approaches. The first approach is the complementary type which involves compressing the audio signal in some well-defined manner before it is recorded (primarily on tape). The second approach is the single-ended or non-complementary type which utilizes techniques to reduce the noise level already present in the source material—in essence a playback only noise reduction system. This approach is used by the LM1894 integrated circuit, designed specifically for the reduction of audible noise in virtually any audio source. Noise reduction is the process of removing noise from a signal. Abstract signal analysis is one of the important areas of research in multimedia applications. Discrete Wa

  Smart Handwritten Recognition Using Deep Learning Abstract: Handwritten character recognition is the detection of characters from images and documents and changes them in machine-readable shape for further processing. The applications of digit recognition include postal mail sorting, bank check processing, form data entry, etc. The heart of the problem lies within the ability to develop an efficient algorithm that can recognize handwritten digits and which is submitted by users by the way of a scanner, tablet, and other digital devices. This paper presents an approach to off-line handwritten digit recognition based on different machine learning techniques. Several machine learning algorithms namely, Convolutional Neural Network, Multilayer Perceptron, Support Vector Machine and K-Nearest Neighbor have been used for the recognition of digits. The main focus of this work is to investigate CNN capability to recognize the characters from the image dataset and the accuracy of recognition