SCILAB

DSP Scilab


 
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FREE DOWNLOAD examples  size: 50 k

Ver. 1.1 / 2013       
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 Nr.11        (no further obligation!)

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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.

Trasfer Function

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.

Bode Diagram

 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.

FFT

A little statistics (regression, interpolation) and 3D display with time-frequency analysis (spectrograph) are also in this eBook for beginners.

SCILAB

FFT

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 


 


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Last Update: 04.04.2020


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DSP

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MATLAB

FFT

IIR

Specrogram

Filter

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