This is a container library for linear filters. It consists of three different container structures:

They all have the same interface, but there are differences in the performance of certain methods.

Creating linear filter structures

import signals.containers-1;

my_tf = new (
  [ new TransferFunction(
	[1,2,3,4,5,6], // numerator of the polynomial
	[7,8,9] // denominator of the polynomial
	,150 Hz // sampling frequency, optional
  ),
  new ZeroPoleGain(
	[1,1,0.5,-0.3], // zeros
	[0,-0.5+0.3j,-0.5-0.3j, 0.95j, -0.95j], // poles
	1 // gain
	,150 Hz // sampling frequency, optional
  )
])
Create Structure

Visualization


my_tf.plotAmplitude(20/* number of points */)
// The Y axis is in logarithmic (dB) scale.
	Amplitude Plot


	my_tf.plotPhase(20/* number of points */)
	Phase Plot


	my_tf.plotZerosPoles()
	Pole-Zero Plot


	my_tf.plotImpulseResponse(20/* number of points */)
	Impulse Response


	my_tf.plot() // plot in the native form
	Plot

plot() has different behaviors in different representations. In the cases of TransferFunction or SignalChain, it plots the amplitude response. In the case of ZeroPoleGain, it plots the pole-zero diagram.

Using the structures

Filtering a test signal

input = [! zeros(100,1), ones(100,1), zeros(100,1), ones(100,1) !]; // test signal
filtered = my_tf.filter(input);
chart().curve(input).curve(filtered)
Filter

Additional functions


// simplified implementation details of the system
my_tf.getImplementationDetails()


// amplitude response as an array
my_tf.amplitude(10 /* number of points */ )


// phase response as an array
my_tf.phase(10 /* number of points */ )


// complex gain as an array
my_tf.complexGain(10 /* number of points */ )


// impulse response as an array
my_tf.impulseResponse(10 /* number of samples */)


// transfer polynomial evaluated at a given point
my_tf.value(0.54)

Converting between representations


// convert any structure to zero-pole-gain
my_tf.toZeroPoleGain()


// convert any structure to transfer polynomial
my_tf.toTransferFunction()


// convert the system to an array of second order IIR filters
my_tf.toSecondOrder()

toSecondOrder() returns a SignalChain structure. It is useful when trying to implement IIR filters and facing stability issues due to quantization.

TransferFunction	Transfer function polynomial.
ZeroPoleGain	The Zero-Pole-Gain representation of the system.
SignalChain	An arbitrary list of the former two.

Containers for linear filters

Using the structures