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How to design Boost converter in MATLAB Simulink

  How to design Boost converter in MATLAB Simulink Matlabhelpers demonstrate how to use the MATLAB software for simulation of Boost converters are mainly used to step up the input voltage to desired values, A boost converters operate on switching mode for the purpose of dc to dc conversion in which output voltage is always greater than input voltage given Introduction to Boost converters Boost converters are mainly used to step up the input voltage to desired values, A boost converters operate on switching mode for the purpose of dc to dc conversion in which output voltage is always greater than input voltage given.it is also known as step up converter this name originated from process of step up transformer where input is stepped up to desire level, On the basis of law of conversion of energy the input power should be equal to output power considering there are no losses. Input power (Pinput) = output power (Poutput) As we know that the output voltage is greater than input voltage Vou
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How to design simulation of PV with Boost converter in MATLAB Simulink

  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
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How to Noise removal from Noisy Audio signal using filters in MATLAB

  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
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Smart Handwritten Recognition Using Deep Learning in MATLAB

  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
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Classification of Diabietic Foot Thermograms using Deep Learning Matlab

  Classification of Diabietic Foot Thermograms using Deep Learning Matlab Abstract According to the World Health Organization (WHO), Diabetes Mellitus (DM) is one of the most prevalent diseases in the world. It is also associated with a high mortality index. Diabetic foot is one of its main complications, and it comprises the development of plantar ulcers that could result in an amputation. Several works report that thermography is useful to detect changes in the plantar temperature, which could give rise to a higher risk of ulceration. However, the plantar temperature distribution does not follow a particular pattern in diabetic patients, thereby making it difficult to measure the changes. Thus, there is an interest in improving the success of the analysis and classification methods that help to detect abnormal changes in the plantar temperature. All this leads to the use of computer-aided systems, such as those involved in artificial intelligence (AI), which operate with highly compl
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Video Stabilization using point feature mapping Matlab

  Video Stabilization using point feature mapping Matlab Abstract: Video capturing by non-professionals will lead to unanticipated effects. Such as image distortion, image blurring etc. Hence, many researchers study such drawbacks to enhance the quality of videos. In this paper an algorithm is proposed to stabilize jittery videos. A stable output video will be attained without the effect of jitter which is caused due to shaking of handheld camera during video recording. Firstly, salient points from each frame from the input video is identified and processed followed by optimizing and stabilize the video. Optimization includes the quality of the video stabilization. This method has shown good result in terms of stabilization and it discarded distortion from the output videos recorded in different circumstances.   INTRODUCTION This example shows how to stabilize a video that was captured from a jittery platform. One way to stabilize a video is to track a salient feature in the image and
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Helmet detection using Deep Learning Matlab

  Helmet detection using Deep Learning Matlab Abstract - Two-wheeler is the most popular modes of transport. Also, it is proved that one of every five bike riders who died on roads were not wearing helmet. This paper proposed a method for motorcycle detection and classification, helmet detection and license plate recognition to detect and identify the motorcyclists without helmet and report it to concerned authorities. Support Vector Machine (SVM) is used for vehicle classification. For helmet detection, CNN algorithms are applied to extract the image attributes, and the SVM classifier is used to classify the objects. For License plate Recognition, Optical Character Recognition (OCR) algorithm is used. The Simple Message Service (SMS) is sent to the helmet rule violators. The results are stored in the Database for further actions. INTRODUCTION Head injuries are the leading cause of death and major trauma for two- and three-wheel motor vehicle users. Travel on a motorcycle carries and a
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