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Signal Processing - Digital Signal Processing

Digital signal processing (DSP) Digital signal processing (DSP) is concerned with representation of signals as numbers and processing of these sequences. DSP has fixed processing characteristics, i.e. they are independent of the external factors of the environment at that moment. No need of a realignment over a life time, component tolerance does not affect the system performances, and no adjustments needed during the time of process, an increase of 1bit in representation results in increasing 6 db, using of standard digital circuits for implementation and also more importantly, multiplexing which describes the same equipment can be shared between several signals are some major advantages of DSP. DSP is applied in different paths such as acoustic acquisition and presentation, signal coding and compression, machine synthesis of signals and also more importantly to the drum device which is to be produced by HEX, Digital sound synthesis. Furthermore there are four major ways
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Signal Processing - Nyquist Sampling Theorem

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Nyquist Sampling Theorem A continuous time signal can be represented in its samples and can be recovered back when sampling frequency f s  is greater than or equal to the twice the highest frequency component of message signal. fs ≥2 fm The Nyquist Theorem, also known as the sampling theorem, is a principle that engineers follow in the digitization of analog signals. For analog-to-digital conversion (A DC ) slices, called  samples , of the analog w aveform  must be taken frequently. The number of samples per second is called the sampling rate or sampling frequency. As tube amplifiers give a more pleasant mutation and compression to musical signals than transistors, analog tape similarly warms up and fattens the sound. Though, it is not needed to refrain from the other different uses of it. Other techniques such as tube compressors, to fatten the sound if needed.  there is no such thing as the  perfect low-pass filter  required by Nyquist’s theorem. A real filt
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