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The encoding of a message is the creation of the message. The decoding of a message is how people can comprehend, and decipher the message. It is a procedure of understanding and interpretation of coded data into a comprehensible form. In this paper, a self-created explicitly defined function for encoding numerical digits into graphical representation is proposed. The proposed system integrates deep learning methods to get the probabilities of digit occurrence and Edge detection techniques for decoding the graphically encoded numerical digits to numerical digits as text. The proposed system’s major objective is to take in an Image with digits encoded in graphical format and give the decoded stream of digits corresponding to the graph. This system also employs relevant pre-processing techniques to convert RGB to text and image to Canny image. Techniques such as Multi-Label Classification of images and Segmentation are used for getting the probability of occurrence. The dataset is created, on our own, that consists of 1000 images. The dataset has the training data and testing data in the proportion of 9 : 1. The proposed system was trained on 900 images and the testing was performed on 100 images which were ordered in 10 classes. The model has created a precision of 89% for probability prediction.

Microgrid is a subsystem comprises of distributed generator (DG) s, non-conventional generators, storage devices and controllable loads. Microgrids are one of the centers for penetration of non-conventional energy resources, storage backup and management of distribution generation units. It results reduction in costs, emission gases, transmission & distribution losses and also conventional energy crisis. Simply it is highly reliable and ecofriendly. In this paper, we present a study of Model Predictive control (MPC) Approach using mixed integer linear programming (MILP) technique while satisfying operational constraints and a time varying requests. MILP technique is used to formulate the Overall optimization problem and commercial solvers are used for substantial improvements in solution quality and computational burden. To assess the performance of the online optimization-based control strategy a microgrid case study is employed and the simulation results are discussed. A modification for above case study was done by considering uncertainties of non-conventional energy. During uncertainties to meet the critical load demand, DG Units are increased. The results show the effectiveness and feasibility of the proposed approach.

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:In this paper we present a non-uniform filter bank (NUFB) matched to a given signal. To obtain matched Mchannel NUFB, first, we choose the decimation set having M-down sampling/decimation factors for which perfect reconstruction NUFB exist and then using novel approach proposed in this paper, M-channel signal matched analysis bank is estimated. The outputs of all filters at the analysis side of proposed filter bank are mutually as well as across various channels are uncorrelated. By using well established theory of multirate filter bank, M-channel NUFB matched to signal is obtained. The equiripple band pass filter will provide better tradeoff compared to previous non uniform Filter bank obtained in this fashion will be useful to compress code or represent the signal or image in the best possible manner.Keywords : filter bank ,NUFB ,PRE IntroductionMany advancements in the area of multirate filter banks in conjunction with the ever increasing numerous applications have made multirate filter banks design an increasingly important field of research. The research effort was first focused on design of a two channel quadrature mirror filter (QMF) bank [1,2], which was later extended to design of Mchannel filter banks [2][3][4][5]. Since then, several techniques [6][7][8][9][10][11] were developed to enhance the performance of filter banks in different engineering fields. Among different types of the filter banks, non-uniform filter banks have been elicited immense interest in the researchers in recent years due to their ability to differentiate information into different frequency bands based on energy distribution of signal which is required for several specific applications. These specific applications include sub-band coding like audio coding, speech coding, data and image compression [1,2]. Uniform filter banks have many constraints like integer and uniform decimation in each sub-band, and limited time frequency resolution. These constraints catalyze the importance of non-uniform filter banks (NUFBs).In addition, NUFBs are able to provide any sort of rational decimation in each channel, any extent of timefrequency resolution as per requirement of the application, less quantization error, and low computational complexity. Over the past few years, a number of design methods [12][13][14][15] have been proposed by different authors for the design of multi-channel filter banks. However, design of a linear