The electrocardiogram (ECG) analysis is commonly used technique in clinical examination proposes a method of designing reconfigurable warped digital filter with various low-pass, high-pass, band-pass and band-stop responses. The warped filter is obtain by replacing each element interruption of a digital filter with an all exceed filter. It is widely used for various video and audio processing applications. Warped filters require first-order all pass conversion to obtain low-pass and high-pass responses, and by using second-order all pass conversion to obtain variable band-pass and band-stop responses. To overcome this drawback, proposed method combines warped filters with the coefficient decimation technique. In VLSI circuits in order to reduce hardware cost Command Signals Decoder (CSD) based shift-and-add approach is used for multiplication. It offers extensive savings in opening count and power utilization more than other approaches.

1. INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 4 ISSUE 2 – APRIL 2015 - ISSN: 2349 - 9303
84
Efficient Design of Higher Order Variable Digital
Filter for Multi Modulated Signals
P.D.Swathika1
PG Scholar, Sona College of Technology,
VLSI Design,
Salem, India1
.
swathikadhanapal@gmail.com
Abstract— The electrocardiogram (ECG) analysis is commonly used technique in clinical examination proposes a method of
designing reconfigurable warped digital filter with various low-pass, high-pass, band-pass and band-stop responses. The warped filter
is obtain by replacing each element interruption of a digital filter with an all exceed filter. It is widely used for various video and
audio processing applications. Warped filters require first-order all pass conversion to obtain low-pass and high-pass responses, and
by using second-order all pass conversion to obtain variable band-pass and band-stop responses. To overcome this drawback,
proposed method combines warped filters with the coefficient decimation technique. In VLSI circuits in order to reduce hardware
cost Command Signals Decoder (CSD) based shift-and-add approach is used for multiplication. It offers extensive savings in opening
count and power utilization more than other approaches.
Index Terms— Variable Digital Filter, Warped Filter, All Pass Filters, Command Signals Decoder
1 INTRODUCTION
Various types of ECG analysis works with
biomedical applications started in late 1950’s, and each year a
greater amount of recording are acquired and analyzed. So,
automatic ECG analysis is a topic that continues to be of
interest in biomedical engineering. The warped filter structure
is designed only with linear-phase FIR and sub-filter
coefficients. These sub-filters are related, with fractional
delays [1]. The filter design is more difficult as the number of
unknown parameters is larger, for (eg). 42686 parameters
with 3048 channels, optimization problem occurs due to the
higher-order design [2]. In order to reduce the channel
parameter, design structure gives 21343 channels. Hence it
posses huge memory resources and complexity of time in
higher-order filters. The transmit function of FIR filter order
which will increase the difficulty [1] [2] and the clean signal
in contribution dispensation sampling rate also increases the
amount of time. The applicability of unknown parameters of
higher-order [3] is designed through filter banks and
fractional delays. The existing technique shows the design of
individual low pass filters and flexible modulated filter banks
[1], with Transmultiplexers TMUX [3] [5]. The major
disadvantage of this method is that it cannot be applicable for
all types of filters and its filter structure. It makes the
implementation of polynomial impulse response [4] respect to
direct form linear-phase FIR filters, with a narrow transition
band is mainly expensive when compared with variable
digital filters. The existing technique that works with
Modified Discrete Fourier Transform MDFT) filter banks are
introduced. It shows the analysis of using synthesis filters
with modulation of complex low-pass prototype filters in
subbands comparisons. The existing mappings of MDFT
filter banks [6], real input signals are converted to complex
subbands signals by the reconstruction of prototypes with
linear-phase structure. Then MDFT filter banks are changed
to complex modulated, critically sub sampled by DFT filter
banks. They combine key features of DFT filter banks as
linear phase analysis and synthesis filters and an efficient
realization with almost [7] Perfect Re-construction
(PR).However in many applications, the functions of the
polyphase components with single-stage structure results in
substantially higher complexity when compared with
proposed formation. Hence the further cost is obtained by
converter block of fractional delay coefficient with delayed
functions [2]. Hence the filter banks works unequally for
conversions of multistage converters which shows poor
flexibility condition. The proposed method includes
reconfigurable warped filter structure with all pass filters are
designed with variable digital filters in order to yield a Fetal
ECG output from MotherECG input signal with
respective cut-off frequencies.

2. INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 4 ISSUE 2 – APRIL 2015 - ISSN: 2349 - 9303
85
2 RELATED WORKS
The concept of farrow structure with fractional
delays was used in order to achieve for [6][7] generating
perfect-reconstruction (PR) multichannel prototype finite-
impulse response. The synthesis of transfer function with
linear-phase FIR is given by
𝐻p(z) = ℎ𝑁
𝑛=0 p n z-n
Where hp [N-n] = hp[n] for n=0, 1 …N. The impulse response
to the transfer function Hk (z) is denoted as the reference
prototype filter followed by Cosine- modulation is
ℎ 𝑘[𝑛]=ℎ 𝑝[𝑛] 2/𝑚 * cos [(k +
1
2
)
𝜋
𝑀
(n-
𝑁
2
) + (-1) k 𝜋
4
]
For generating PR with CMFB based prototype filters for
given number channels, in order to guarantee PR condition
independent. The values of these design unknowns are
selected with its requirements. Based on prototype filter PR
with CMFB has no constraints to minimize the objective
function. These facts are unable to use of any effective
unconstrained prototype filters. However, due to the fact of
these problems, the convergence with local optimum solution
implies a poor enough in linear-phase FIR structure.
3 EXISTING METHODOLOGY FARROW
STRUCTURE
The Farrow Structure is used to express the filter
design of a linear phase FIR [1]. Methods of designing these
high-order normalized filters are prototype filter banks (FB’s)
and transmultiplexers (TMUX) with large number of
channels. Here the performance of filter is not analyzed. The
farrow structure consists of sub filters with different set SL (z)
= 0, 1….L.
Fig.1. Farrow Structure
By using 16-bit multipliers in each filter tap consume
large area and power. Hence overall throughput is very poor
in multiplier based approach and it has less accuracy in
computing difference between input and reference signal in
filter block. Linear-phase FIR filters irrespective of its
regulate being high, low, even, or odd as well as the impulse
response being symmetric or antisymmetric. However, it is
more difficult for filters with high orders as the conventional
design of such filters is more challenging. High
computational delay shows implementation complexity is
high. The order of a linear-phase finite-length impulse
response (FIR) low pass filter depends on its transition band,
i.e., the difference between the pass band and stop band
edges, as well as the pass band/stop band ripples. In both
cases, the filter order is more sensitive to the transition band
rather than the ripples. After estimating the filter order, one
must solve an optimization problem to determine the filter
coefficients. For high filter orders, e.g., 32767 which is used
in a cosine modulated filter bank (CMFB) with 2048 channels
the filter design becomes difficult as the number of [6][7]
unknown parameters is large. Relations between the filter
order and the number of FB channels, is not crucial. In other
words, the main aim to show the effectiveness of obtaining
filters with high orders. To overcome this drawback,
proposed method includes variable digital filters for multi-
modulated processing with flexible input coefficients.
4 PROPOSED METHODOLOGY
Direct Arithmetic (DA) based approach is used for
filter convolution with this approach we can increase the filter
response speed without adding any hardware complexity. For
sharp filter response requires a large number of coefficients
(impulse responses). This will increase the filter length and
more filter taps are required for computation. Here through
decimation factor taps used for filter output is changed
dynamically.
4.1 Proposed Variable Digital Filter
Variable Digital Filters (VDF) is digital filters with
controllable spectral characteristics such as cutoff frequency
response, adjustable pass band width, and controllable
fractional delays. They found applications in different areas
of signal processing and communications, e.g. fractional
delay digital filters for timing adjustment in digital receivers.
In proposed system, variable digital filters are designed by
using warped filter structure. Variable digital filters is a filter
whose frequency response specifications, cutoff frequency fc
can be controlled through number of parameters with
minimum overhead on complexity. Methods for designing
variable digital filters are done by using conversion method.
Certain conversion such as all pass conversion is then applied
to VDF with variable cutoff frequencies. The coefficients of
the polynomials are then determined to provide continuous
tuning of the VDF by conversion. The z-domain transfer
function obtained from the bilinear transform is at best a good
approximation of the analog frequency response. As the input
frequency increases toward fs/2, the digital filter response
becomes less representative of the analog frequency response.
The decimation technique is denoted by the simplest
resampling technique because it involves reducing the
number of samples per second required to represent a signal.
If the input signal is strictly band limited such that the signal
spectrum is zero for all frequencies above fs/ (2M), then
decimation can be performed by simply retaining every M-th
sample method.
μμμ
y (n)
x (n)
SL(z) S2(z) S1(z) S0(z)

3. INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 4 ISSUE 2 – APRIL 2015 - ISSN: 2349 - 9303
86
Fig.2. Block Diagram of VDF
4.2 Warped α- Coefficient Frequency Variation
Warped filter is obtained by replace each unit
impediment of a digital pass through a filter with all-pass
structures of an appropriate order. Therefore by changing the
coefficients of an all pass filters, the fc can be controlled.
Fig.3. Warped digital filter
Warped filters bandwidth needs to be changed, to update the
filter coefficients which will incur a large number of memory
read and write operations. Depending on the application,
warped filters with response of low-pass, high-pass, bandpass
or bandstop are designed. Here alpha is a set of constants
used to vary the cutoff frequency selections of all pass filters.
4.3 Frequency Responses of All Pass Filters
Design
A filter bank designed using warped filters is
proposed for all pass filters. The low pass, band pass, and
high pass filters are connected in parallel. However, the
complexity of the band pass filter uses second-order all pass
conversion.
Fig.4.Single multiplier structure for A (z)
The approximation function is assumed to be a linear
combination of filter structure. Without loss of complexity, a
tunable adaptive filter using a piecewise polynomial yields
tunable FIR VDF with good frequency characteristics and
offers larger tuning range than ordinary polynomial-based
approach.
They include conversion based on warped filter and
frequency response masking based approach. Coefficient
decimation (CDM) technique for realizes the low-complexity.
VDFs with fixed coefficients are designed using warping
technique to detect bandpass signals in a broadband signal.
The variable frequency of α coefficients are obtained as
Low-pass frequency responses are obtained using the all pass
transformation given by
G (z) = H (A (z)). Where A (z) = (
−𝛼+𝑧−1
1−𝛼𝑧−1 ) |α| < 1
High-pass frequency responses are obtained using the all
pass transformation given by
G (z) = H (-A (z)).
Fixed bandwidth band-pass responses at an arbitrary center
frequency are obtained by using the reduced second order
transformation given as
G (z) = H (B (z)). B (z) = -z-1
(
−𝛼+𝑧−1
1−𝛼𝑧−1
)
Where |α| < 1 = -z-1
A (z).
Fixed bandwidth band-stop responses at an arbitrary center
frequency are using the transformation given as
G (z) = H (-B (z)).
In proposed VDF, there are two controlling parameters used
such as warping coefficient α and decimation factor M. Both
the parameters control the cutoff frequency α controls the
center frequency and M controls the bandwidth |α| < 1 and M
can be used as a positive integer. In the same way, different
kinds of variable responses can be obtained using fixed
coefficient filter architecture.
4.4 Fetal ECG Extraction
The adaptive algorithms for FIR filters are widely
used in various applications such as medicine, statement and
have power over due to its easily performance, strength and
best presentation. Its simplicity makes it attractive for ECG
analyses where it is need to minimize MECG error response.
Filters take part in a significant role for exclusion of
_
+
+
+
OutputInput
OutputInput Z-1
𝛼
Z-1
A (Z)
Y (n)
X (n)
𝛼
h0 h1 h2 hn
A(Z) A(Z) A(Z)
Fs2Fs1
Frequency
selection
All pass filter
structure using
MUX
Extracted
FECG
output
Alpha value for cut
off frequency
selection
MECG input
signal
Input filter
coefficients
M-Decimation
factor

4. INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 4 ISSUE 2 – APRIL 2015 - ISSN: 2349 - 9303
87
redundant signal or clamor from unique input signal in FECG
extraction by removing the selected frequencies from the
incoming signal. These FECG signals become much popular
due to the amplification of the digital signal processing. Here
a comparator is used to acquire finite response between input
signal and desired response signal. The comparator output is
reorganized in LUT and multiplied with samples as filter
coefficients.
4.5 Adaptive Filters with Low Complexity
Filters are used in application of biomedical
instruments, as the frequency response of medical instrument
are extremely small and so digital filters are much accepted
for low rate of recurrence application. The manipulative of
the adaptive filter, it’s balanced to choose the adaptive filter
algorithm for high accuracy. Here LMS algorithm is
proposed with AFIR for Fetal ECG extraction, which will be
interior causative factor for the achievement of algorithm
functioning. For any purpose of the adaptive filters, the
contribution signal and the orientation effort is essential to
individual progression. The smallest amount indicates
squaring method is use to regulate the influence of the
adaptive filter in order to decrease the error. The best
explanation to remove the unnecessary signal or noise from
the participation signal is the suggestion noise must be
cleaned out by means of adaptive filtering technique due to
its good concert and consistency. The filter coefficients in
adaptive filtering are a set of constants which is used to
multiply delayed signal samples inside the structure. FIR
filter is terminated by its transfer function and the filter order
is merely the number of taps multiplied by MAC unit, if
suppose response is working until now the desire reaction is
said to be finite, the filter still is a FIR. This pass through a
filter have a limited desire response constant while it uses
opinion after N samples of an desire function represented in
digital filtering.
5. SIMULATION RESULTS & ANALYSIS
Fig.5. Simulation of MECG
The above figure shows the reference signal and input signal
obtained from MECG samples. The sample is loaded into an
on chip memory with width 15bit and depth of 1000 and
applied to internal logical blocks by using a sequential 10bit
counter. The output shows the testbench wave forms in
which the signal coefficients have been fixed. Simulation is
obtained using modelsim simulator.
Fig.6. Simulation of FECG Extraction
The figure shows accurate fetal ECG extracted from MECG.
Low frequency component and distortions are removed using
HP filter and genetic algorithm by coefficient replacement.
Based on its time and frequency, the conditions of fetal can
be analyzed.
6 RESULTS AND DISCUSSION
The input MECG signal is referred to the
concentration of detecting QRS- complex with adaptive
equalization of binary test noise obtained by warped filters.
This is the prominent feature in ECG recordings and it is still
deemed to be useful information about the heart status of
patients recently more complete algorithms that allow the
computation of other essential ECG parameters have been
developed.
Fig.7. Result of FECG separation.

5. INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 4 ISSUE 2 – APRIL 2015 - ISSN: 2349 - 9303
88
7. CONCLUSION
In this paper, variable filter design using warped
filters has been presented. Most of these VDFs are commonly
used for communication applications due to their exact
characteristics of warped structure with all pass filters and
flexible input coefficients. It has been considered to denoised
the filters from the noisy input signal with application of
FECG signal get separated from MECG distortion less output
obtained from all pass filter coefficients through reference
input capitulate to get FECG output By using these proposed
technique, FECG signal is denoised and low complexity,
accuracy is achieved. All simulation results are carried out by
using modelsim software.
REFERENCES
[1] Amir Eghbali and Håkan Johansson,” On efficient
design of high-order filters with applications to filter
banks and transmultiplexers with large number of
channels”, IEEE Trans, on signal processing, vol. 62,
no. 5, march 1, 2014.
[2] H. Johansson and O. Gustafsson,“Linear-phase FIR
interpolation, decimation, and M-th band filters utilizing
the Farrow structure” IEEE Trans. Circuits Syst. I, vol. 52,
no. 10, pp. 2197-2207, Oct. 2005.
[3] M. B. J. Furtado, P. S. R. Diniz, S. L. Netto, and T.
Saramäki “On the design of high-complexity cosine-
modulated transmultiplexers based on the frequency-
response masking approach” IEEE Trans. Circuits Syst. I,
vol. 52, no. 11, pp. 2413–2426, Nov. 2005.
[4] R. Lehto, T. Saramäki, and O. Vainio “Synthesis of
narrowband linear-phase FIR filters with a piecewise-
polynomial impulse response” IEEE Trans. Circuits Syst.
I, vol. 54, no. 10, pp. 2262–2276, Oct. 2007.
[5] P.Martin-Martin, R. Bregovic, A. Martin-Marcos, F.
Cruz-Roldan, and T. Saramäki, “A generalized window
approach for designing transmultiplexers,” IEEE Trans.
Circuits Syst. I, vol. 55, no. 9, pp. 2696–2706, Oct. 2008.
[6] T. Karp and N. J. Fliege, “Modified DFT filter banks
with perfect reconstruction,‖IEEE Trans. Circuits Syst. II,
vol. 46, no. 11, pp. 1404–1414,Nov. 1999.
[7] R. Bregovic and T. Saramäki, ―A systematic technique for
designing linear-phase FIR prototype filters for perfect-
reconstruction cosine- modulated and modified DFT filter
banks,‖ IEEE Trans. Signal
Process. vol. 53, no. 8, pp. 3193–3201, Aug. 2005.
[8] T. Ihalainen, T. H. Stitz, M. Rinne, and M. Renfors,
―Channel equalization in filter bank based multicarrier
modulation for wireless communications,‖ EURASIP J. Appl.
Signal Process, vol. 2007, 2007, Article ID 49389.