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Speed improvement in Digital signal processing is considered to be challenging. High speed multipliers and adders are prime requirement for digital filters and for FFT operations.Vedic mathematics is an ancient scheme based on 16 formulas (sutras). These are simple and easy methods which can be directly applied for DSP computations. Many researchers have worked on multiplier designs using Vedic operators. Present paper deals with exhaustive review of literature based on Vedic mathematics. It shows that Vedic mathematics can be used for fast signal processing. Multipliers based on Vedic mathematics can be used for speed improvement, reduction in power consumption, complexity, area etc. Vedic mathematical algorithms can be proved efficient over traditional (existing) methods in FIR and IIR filters for providing effective results in de-noising of biomedical Signal.

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Current state of emotion of a person is highly related to what entertainment content he/she want to listen or watch. An emotion-based content recommendation will help the user to not only to get content according to their current state of mind but also reduce the efforts of managing a playlist for music and help them reduce their stress level by recommending them appropriate content for stress relief. Emotion of a person can be determined using his/her facial expression. This facial expression can be detected using a machine learning model, we have developed a model using xception architecture. An application which will access the camera of the device and take image of the persons face, it will connect to the ML Kit stored on the cloud (Firebase) which will analyze the image and detect the mood of the user, from that mood it will connect to API of a music and movies application (E.g., Spotify, Netflix, Disney Hotstar, etc.), though which we will recommend the content. The application will also verify from the user for his/her taste of music and customize the recommendation accordingly. The user will be prompted for change in emotion after specific intervals if he/she likes to change the content.