SignalUtils.ExpAverageFilter Method

Overload List

#	Signature	Description
1	void ExpAverageFilter(TVec Data, ref TCplx State, Double Decay)	Filter data with an exponential average filter.
2	void ExpAverageFilter(TVec Data, ref Double State, Double Decay)	Filter data with an exponential average filter.
3	void ExpAverageFilter(Double Decay, TVec Num, TVec Den)	Design an exponential filter with Decay parameter and place the transfer function in Num (numerator) and Den (denominator).
4	Double ExpAverageFilter(Double Data, ref Double State, Double Decay)	Filter data with an exponential averaging filter.

Overload 1: void ExpAverageFilter(TVec Data, ref TCplx State, Double Decay)

Filter data with an exponential average filter.

#	Name	Type	Description
1	Data	TVec	source TVec
2	State	TCplx (ref)	output
3	Decay	Double	scalar

Result: stored in self (calling object)

Remarks:

Exponential average filter without the TIirState structure for complex data.

Overload 2: void ExpAverageFilter(TVec Data, ref Double State, Double Decay)

Filter data with an exponential average filter.

#	Name	Type	Description
1	Data	TVec	source TVec
2	State	Double (ref)	output
3	Decay	Double	scalar

Result: stored in self (calling object)

Remarks:

Exponential average filter without the TIirState structure. The function can be called to filter sample by sample. Initialize the State to 0 on the first call. Decay defines the decay from sample to sample and is initialized to 50% by default. With each new sample, the filter will take average from the 50% of the new sample and 50% of the previous average. The exponential average filter implements the following difference equation:

y[i] = 1/d * x[i] + (d-1)/d * y[i-1]

x.. input signal
y.. output signal
d.. Decay factor

In terms of percentage:

y[i] = a * x[i] + b * y[i-1] ,   a + b = 1

a*100 ... percent of the new data used.
b*100 ... percent of the old average used to compute the new average.

Overload 3: void ExpAverageFilter(Double Decay, TVec Num, TVec Den)

Design an exponential filter with Decay parameter and place the transfer function in Num (numerator) and Den (denominator).

#	Name	Type	Description
1	Decay	Double	scalar
2	Num	TVec	source TVec
3	Den	TVec	source TVec

Result: stored in self (calling object)

Remarks:

Transfer function can be used to initialize an IIR filter by passing num and den to the IirInit routine.

Examples

using Dew.Math;
    using Dew.Math.Editors;
    using Dew.Math.Units;
    using Dew.Signal;
    using Dew.Signal.Units;
    using Dew.Math.Tee;
    using Dew.Signal.Tee;


    private void button1_Click(object sender, EventArgs e)
    {
        Vector b;
        Vector c = new Vector(0);
        Vector num = new Vector(0);
        Vector den = new Vector(0);

        int n;
        int i;

        TIirState IirState = new TIirState();
        double state;

//Alternative 1: Tone with 5 periods
//      b := Math387.Sin(Ramp(300, mvDouble, 0,2*Pi*5/300));

//Alternative 2: Gaussian noise
    b = MtxExpr.RandGauss(300,false);
    c.Copy(b);
    n = 10;
    state = 0;
    int bLength = b.Length;
    for (i = 0; i < (bLength / n); i ++) //streaming test 1
    {
        b.SetSubRange(i*n,n);
        SignalUtils.ExpAverageFilter(b,ref state, 10); //set to 10%
    }
    b.SetFullRange();
    MtxVecTee.DrawIt(new TVec[2] {c,b}, new string[2] {"Unfiltered","Filtered"},"Exponential averaging",false);

    b.Copy(c);
    SignalUtils.ExpAverageFilter(10,num,den); //set to 10x, (1/10 = 0.1, => 10%)

    SignalUtils.IirInit(num,den,ref IirState,false);
    bLength = b.Length;
    for (i = 0; i < (bLength / n); i ++) //streaming test 2
    {
        b.SetSubRange(i*n,n);
        c.SetSubRange(i*n,n);
        SignalUtils.IirFilter(b,c,ref IirState);
    }
    SignalUtils.IirFree(ref IirState);

    b.SetFullRange();
    c.SetFullRange();
    MtxVecTee.DrawIt(new TVec[2] { b, c }, new string[2] { "Unfiltered", "Filtered" }, "Exponential averaging with IirFilter", false);
    }

Overload 4: Double ExpAverageFilter(Double Data, ref Double State, Double Decay)

Filter data with an exponential averaging filter.

#	Name	Type	Description
1	Data	Double	scalar
2	State	Double (ref)	output
3	Decay	Double	scalar

Returns: Double

Remarks:

Single sample non-vectorized variant of the exponential averaging.