 Ver. 1.1 / 2013        eBooks only for WINDOWS! Nr.11        (no further obligation!) The basics of Digital Signal Processing (DSP) with the tool SCILAB are explained step by step in this eBook with 150 pages. We need to understand such equation, as shown below, but it is used only as much math as needed. The focus here is on the practical application of SCILAB functions and is aimed at beginners who wanted to apply DSP algorithms. The functioning of SCILAB is explained in films as examples below. We will also the so seemingly simple methods, such as average totals, min/max and so on discusse. We get to differentiate and integrate but thats not so hard with the FREE tool SCILAB, which we will use for all examples. We will use digital filters (FIR and IIR) and therefore we need such equations as shown above. Professionally to make the digital filter, we must use the frequency analysis with FFT and understand. A little statistics (regression, interpolation) and 3D display with time-frequency analysis (spectrograph) are also in this eBook for beginners.  Content (1) Analog signals    Signals    Analog Signals    Digital Signals    Processing signals    Analog time    Discrete time  (2) Sample analog signal    Introduction    Start SCILAB    Variables    Analog signal    Signal and sampling time    Sampling time vector    Sample sine signal    Variables Browser    Add three sine signals    Current directory    Writing a script    PLOT multiple signals    Shannon Law    Sampling frequency 1000Hz    Alias Frequencies    Alias Frequenzen    Don't forget!    The highest frequency in the signal    (3) Quantization    A/D-Converter    8 Bit, 10 Bit, 12 Bit etc.    Sampling and A/D converter    Antialias LP filter    Save measurement data    Measurement data Copy and Paste    Create time vector    Copy matrix    Load ASCII data    Load ASCII data with text    Zeilen und Spalten    Load WAV data    Save/load data binary  (4) Measurement data analysis    Online and Offline    Move on Y-Scale    Move on X-Scale    Cut/attach    Add row and column vector    Normalize/Scale    Min/Max and average value    Differentiate    Integrate    Integration via sampling times    SUM is not so exact!    TRAPEZ is better    Integrate with INTTRAP()    Integrate with INTTRAP()    Lineare Regression    Lineare Interpolation    Nonlinear interpolation    Nonlinear regression    Histogram    Random numbers    Mean value    Mean value sliding   (5) Average value as filter    The FOR loop    Past and future values    Start/Stop Problem    Number of factors    Factors different    Factors different    Step response    Frequency behaviour    Bode-Diagram    Amplitude response    Decibel    Cut-off frequency    Phase response    PLOT and PLOT2D    FIR and IIR Filter  (6) FIR and IIR Filter    Filter    Filters with and without feedback    Transfer function    Filter properties    Standardized frequencies    Apply filter    Design of FIR filter    Sine as test signal    wfir( ) Funktion    LP-Filter with wfir()    LP-Filter with wfir()    Decrease filter order    Change cut-off frequency    FFT-Spectrum    Filter Amplitude response    Signal and filter spectrum    FIR high-pass filter    FIR Band-Pass Filter    FIR band rejection filter    WFIR() interactive    ffilt() Function    eqfir() Function    LP-Filter with eqfir()    HP-Filter with eqfir()    BP-Filter with eqfir()    Bode-Diagram    IIR Funktionen    iir() Function    iir() Function    Filter order    cut-off frequency    IIR HP-Filter    IIR BP-Filter    EQIIR() Function  (7) FFT Frequency Analysis    Spectrum    Square wave signal from oscillations    Ideal FFT    FFT not so ideal!    Distance of the spectral lines    The more sampling points the better    Too few sampling points    Frequency spacing does not fit    Periodicity    Window    Hamming Window    Kaiser Window    FFT does not really fit!    Narrow and broadband analysis    Inverse FFT    FFT and random signals    FFT and random signals    Power spectrum    Power spectrum Example    U * U = FFT * FFT    PSPECT Function    Power density spectrum PSD  (8) Spectrogram    One impulse    Two pulses    Frequency-time analysis    Animation    Time-Frequency Toolbox    Two sine signals    The first example    Amplitude modulation    Frequency modulation    FFT Frequency modulation    STFT Frequency modulation    STFT Menu    Sine modulation    Time-frequency resolution    Time-frequency resolution    STFT Power density email@ebookaktiv.de © 2003-2020    ebooksmechatronic.com Last Update: 04.04.2020

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DSP

SCILAB

MATLAB

FFT

IIR

Specrogram

Filter

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