mfilt.firinterp
(Removed) FIR filterbased interpolator
Compatibility
mfilt.firinterp
has been removed. Use dsp.FIRInterpolator
instead. For more details, see Version History.
Syntax
Hm = mfilt.firinterp(L)
Hm = mfilt.firinterp(L,num)
Description
Hm = mfilt.firinterp(L)
returns a FIR
polyphase interpolator object Hm
with an interpolation factor of
L
and gain equal to L
. L
defaults to 2 if unspecified.
Hm = mfilt.firinterp(L,num)
uses the values
in the vector num
as the coefficients of the interpolation
filter.
Make this filter a fixedpoint or singleprecision filter by changing the value of the
Arithmetic
property for the filter Hm
as
follows:
To change to singleprecision filtering, enter
set(hm,'arithmetic','single');
To change to fixedpoint filtering, enter
set(hm,'arithmetic','fixed');
Input Arguments
The following table describes the input arguments for creating
hm
.
Input Argument  Description 

 Interpolation factor for the filter. 
 Vector containing the coefficients of the FIR lowpass
filter used for interpolation. When 
Object Properties
This section describes the properties for both floatingpoint filters (doubleprecision and singleprecision) and fixedpoint filters.
FloatingPoint Filter Properties
Every multirate filter object has properties that govern the way it behaves when
you use it. Note that many of the properties are also input arguments for creating
mfilt.firinterp
objects. The next table describes each
property for an mfilt.firinterp
filter object.
Name  Values  Description 


 Defines the arithmetic the filter uses. Gives you the
options 
 Character vector  Reports the type of filter object. You cannot set this
property — it is always read only and results from your
choice of 
 Integer  Interpolation factor for the filter. 
 Vector  Vector containing the coefficients of the FIR lowpass filter used for decimation. 

 Determines whether the filter states get restored to zeros
for each filtering operation. The starting values are the values
in place when you create the filter if you have not changed the
filter since you constructed it.


 Contains the filter states before, during, and after filter operations. States act as filter memory between filtering runs or sessions. 
FixedPoint Filter Properties
This table shows the properties associated with the fixedpoint implementation of
the mfilt.firinterp
filter.
Note
The table lists all of the properties that a fixedpoint filter can have. Many of the properties listed are dynamic, meaning they exist only in response to the settings of other properties. To view all of the characteristics for a filter at any time, use
info(hm)
where hm
is a filter.
For further information about the properties of this filter or any
mfilt
object, refer to Multirate Filter Properties.
Name  Values  Description 

 Any positive or negative integer number of bits. [32]  Specifies the fraction length used to interpret data output
by the accumulator. This is a property of FIR filters and
lattice filters. IIR filters have two similar properties
— 
 Any integer number of bits[39]  Sets the word length used to store data in the accumulator. 
 fixed for fixedpoint filters  Setting this to 
 [true], false  Specifies whether the filter automatically chooses the
proper fraction length to represent filter coefficients without
overflowing. Turning this off by setting the value to

 Any integer number of bits [16]  Specifies the word length to apply to filter coefficients. 
 [FullPrecision], SpecifyPrecision  Controls whether the filter automatically sets the output
word and fraction lengths, product word and fraction lengths,
and the accumulator word and fraction lengths to maintain the
best precision results during filtering. The default value,

 Any positive or negative integer number of bits [15]  Specifies the fraction length the filter uses to interpret input data. 
 Any integer number of bits [16]  Specifies the word length applied to interpret input data. 
 Any positive or negative integer number of bits
[  Sets the fraction length used to interpret the numerator coefficients. 
 Any positive or negative integer number of bits [32]  Determines how the filter interprets the filter output
data. You can change the value of

 Any integer number of bits [39]  Determines the word length used for the output data. You
make this property editable by setting

 saturate, [wrap]  Sets the mode used to respond to overflow conditions in
fixedpoint arithmetic. Choose from either

 [  Sets the mode the filter uses to quantize numeric values when the values lie between representable values for the data format (word and fraction lengths).
The choice you make affects only the accumulator and output arithmetic. Coefficient and input arithmetic always round. Finally, products never overflow — they maintain full precision. 
 [true], false  Specifies whether the filter uses signed or unsigned fixedpoint coefficients. Only coefficients reflect this property setting. 

 Contains the filter states before, during, and after filter
operations. States act as filter memory between filtering runs
or sessions. The states use 
Filter Structure
To provide interpolation, mfilt.firinterp
uses the following
structure.
The following figure details the signal flow for the direct form FIR filter
implemented by mfilt.firinterp
. In the figure, the delay line updates
happen at the lower input rate. The remainder of the filter — the sums and
coefficients — operate at the higher output rate.
Examples
This example uses mfilt.firinterp
to double the sample rate of a
22.05 kHz input signal. The output signal ends up at 44.1 kHz. Although
l
is set explicitly to 2
, this represents the
default interpolation value for mfilt.firinterp
objects.
L = 2; % Interpolation factor. Hm = mfilt.firinterp(L); % Use the default filter. fs = 22.05e3; % Original sample freq: 22.05 kHz. n = 0:5119; % 5120 samples, 0.232s long signal. x = sin(2*pi*1e3/fs*n); % Original signal, sinusoid at 1 kHz. y = filter(Hm,x); % 10240 samples, still 0.232s. stem(n(1:22)/fs,x(1:22),'filled') % Plot original sampled at % 22.05 kHz. hold on; % Plot interpolated signal (44.1 kHz) in red stem(n(1:44)/(fs*L),y(25:68),'r') xlabel('Time (sec)');ylabel('Signal Value') legend('Original Signal','Interpolated Signal');
With interpolation by 2, the resulting signal perfectly matches the original, but with twice as many samples — one between each original sample, as shown in the following figure.