Cosine-modulated Filter Banks Research Articles

Designing optimal prototype filters for maximally decimated Cosine Modulated filter banks with rapid convergence

An analytic design of a prototype filter for M-channel maximally decimated cosine-modulated Near Perfect Reconstruction (NPR) filter banks is proposed in this work. The prototype filter is created using the least-square (CLS) method with weighted constraints, which is one-dimensional and requires single-parameter optimization. Compared to existing approaches, this suggested method achieves rapid convergence by analytically determining the optimal step size, ensuring the 3 dB cutoff frequency at π/2 M. The simulation results for design examples outperform the techniques in the available literature in terms of amplitude and aliasing distortion, reaching distortion around 2.4489 × 10−4 and 3.4907 × 10−9, respectively. This optimization algorithm's usefulness is further demonstrated with the sub-band coding of ECG signals. Implementing optimal prototype filters has tangible real-world effects, especially in critical sectors like healthcare and communications, improving diagnostics accuracy, data transmission efficiency, and overall performance.

Multicarrier technique for 5G massive MIMO system based on CDMA and CMFB

Filterbank multicarrier (FBMC) is an effective method for modulation over massive multiple-input multiple-output (MIMO) channels in the future fifth generation wireless networks. This multicarrier technique provides high spectral efficiency, and it is resilient against synchronization errors compared to the well-known orthogonal frequency division multiplexing technique. This paper introduces a new technique, that combines the Code-division multiple-access (CDMA) and cosine modulated filter banks, a specific class of FBMC, to massive MIMO communication systems. In the proposed technique, the data symbols are transmitted on different sub-bands and also, they are spread in each sub-band by CDMA code. The proposed technique reduces the interference between data symbols, which consequently improves bit-error-rate (BER) performance. Simulation results show that the overall BER performance of the proposed multicarrier transmission technique is significantly enhanced. The results obtained show that as the number of base station antennas increases, different channel distortions are averaged out, thus BER decreases (in average by 10–2) for the same signal-to-noise ratio.

Design of uniform cosine modulated filter bank using [formula omitted] and its application in baseline wander removal from ECG signal

In this paper, a uniform cosine modulated filter bank (CMFB) is designed using the Incremental Ant Colony Optimization with Local Search (IACOR-LS) and utilized for the removal of Baseline Wander (BW) from the ECG signal. Here, for the CMFB design, a prototype filter is designed with window function having shape parameter ‘α’ and its cut-off frequency (ωc) is optimized to reduce the amplitude distortion and aliasing errors. It is observed that the proposed method performed better in terms of aliasing errors with higher values of ‘α’. In the continuation, a simple technique is proposed for BW removal from ECG in which the minima of the first sub-band signal of 8-channel uniform CMFB are used to estimate the BW. Four parameters, i.e., Mean Square Error (MSE), Correlation Coefficient (CC), L_Operator (LO) and Absolute Maximum Distance (AMD) are evaluated and compared with the existing methods. It is observed that the proposed technique for BW removal outperformed the existing methods.

ECG signal based automated hypertension detection using fourier decomposition method and cosine modulated filter banks

The leading interest of this study is to develop an automated diagnosis system for detection of hypertension by making use of Electrocardiogram (ECG) signal. In this work, the ECG signal is decomposed using Fourier Decomposition Method (FDM) and uniform Cosine Modulated Filter Bank (CMFB) into eight Fourier intrinsic band functions (FIBF’s) and 8-channel respectively. After decomposition, signal mobility and Log-energy entropy features have been evaluated for the decomposed sub-signals. This feature set of each sub-signal is then given as input to a various classifiers such as K-Nearest Neighbour (KNN), Decision Tree, Ensemble Bagged Tress (EBT) and their performance comparison has also been done in this study. From the results, it has been observed that the highest classification accuracy of 99.91% using FDM has been obtained with area under the curve as 1.0 and KNN as the classifier and an accuracy of 99.99% with area under the curve as 1.0 has been obtained using CMFB and KNN as the classifier. The systems have been cross validated using 10-fold cross validation. The proposed method outperformed the existing methods and hence establish the efficacy of our proposed system over the earlier techniques.

New efficient subband structures for blind source separation

Convolutive mixtures of signals generated by more than one source and acquired by a set of microphones are commonly found in acoustic signal processing applications. Subband methods have been proposed to reduce computational complexity and improve the convergence rate of adaptive algorithms developed for blind source separation of these mixtures, without significantly impairing steady-state performance. Oversampled discrete Fourier transform (DFT) filter bank is a usual option for the generation of subband signals in order to avoid harmful aliasing effects, thereby maintaining sufficient samples to estimate the subband signal statistics. In this paper, two new subband structures, composed of cosine-modulated filter banks (CMFB) with critical or oversampled sampling and low-order adaptive subfilters, are proposed for efficient blind source separation approach in convolutive mixtures of speech signals. A time-varying step-size procedure that provides better convergence rate for several reverberation characteristics is advanced. In addition, both computational complexity and steady-state performance of the proposed structures are compared to those of the standard fullband algorithm, to other subband structures with oversampling and critical sampling, and to frequency domain algorithm. The advanced solutions are capable of improving the source interference ratio (SIR) by more than 5 dB. Finally, two strategies are presented to minimize the effects of remaining aliasing in the proposed subband approaches, which obtain an additional gain of about 3 dB in the asymptotic SIR.

Design of Low-Complex Linear-Phase Non-uniform Filter Bank to Realize Wavelet Approximation of Bark Frequency Partitioning for Real-Time Applications

This paper proposes the realization of perceptual wavelet approximation of Bark scale using a linear-phase integer decimated non-uniform filter bank (IDNUFB), designed by merging the channels of a partially cosine-modulated uniform filter bank. In effect, the channels with different sampling factors of the IDNUFB can be derived from the same prototype filter using the proposed method of design. Also, the proposed IDNUFB is employed for the realization of Bark frequency partitioning. The proposed method of IDNUFB design using PCM and merging is found to have linear-phase property and reduced hardware complexity, when compared to the existing filter bank-based methods for Bark frequency partitioning.

Implementation of Cosine Modulated Digital Filter Bank on Processor with ARM Architecture

This paper presents a class of multichannel cosine-modulated filter banks (CMFB) of analysis based on the modulation effect with a fast discrete-cosine transformation of the fourth type (DCT-IV), which is calculated using the fast Fourier transform. As a prototype filter, a low-frequency filter with a finite pulse characteristic was used, frequency-shifted copies of which were made using an effective technology for polyphase representation of the filter Bank. The comparison of the number of arithmetic operations performed by digital down converter (DDC) based on cascade integral-comb (CIC) and CMFB based on different number of channels is given. A software description of the CMFB algorithm is presented in the form of block diagrams describing the capabilities of the Opencl and clfft software libraries for implementing the DCT-IV filter Bank and modulation algorithm on a GPU. The obtained algorithm was tested on an ARM family processor and a mali GPU with a table with sample rate for different number of channels with the maximum load of the graphics processor (GPU) and the minimum load of the Central processor (CPU).

Application of Nature Inspired Evolutionary Algorithm Optimization Techniques in Design of Cosine Modulated Filterbanks

Application of Nature Inspired Evolutionary Algorithm Optimization Techniques in Design of Cosine Modulated Filterbanks

Design of sparse cosine modulated filter banks based on Hopfield neural network

Cosine modulated filter bank (CMFB) is the most basic and important module in multi-rate signal processing system. Sparse FIR linear-phase CMFB can not only reduce the complexity of hardware design, but also ensure good performance. In this paper, a new design method of CMFB is proposed. First, the set of sparse coefficients of the prototype filter is found by using the orthogonal matching pursuit (OMP) algorithm. Then the Hopfield neural network (HNN) is employed to optimize the non-zero coefficients. The analytical and simulation results demonstrate that the new approach not only ensures that the sparse CMFBs satisfy near perfect reconstruction (NPR), but also improves the efficiency of hardware operation.

Computationally Efficient Cosine Modulated Filter Bank Design for ECG Signal Compression

In this work, computationally efficient and reliable cosine modulated filter banks (CMFBs) are designed for Electrocardiogram (ECG) data compression. First of all, CMFBs (uniform and non-uniform) are designed using interpolated finite impulse response (IFIR) prototype filter to reduce the computational complexity. To reduce the reconstruction error, linear iteration technique is applied to optimize the prototype filter. Then after, non-uniform CMFB is used for ECG data compression by decomposing ECG signal into various frequency bands. Subsequently, thresholding is applied for truncating the insignificant coefficients. The estimation of the threshold value is done by examining the significant energy of each band. Further, Run-length encoding (RLE) is utilized for improving the compression performance. The method is applied to MIT-BIH arrhythmia database for performance analysis of the proposed work. The experimental observations demonstrate that the proposed method has accomplished high compression ratio with the admirable quality of signal reconstruction. The proposed work provides the average values of compression ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), quality score (QS), correlation coefficient (CC), maximum error (ME), mean square error (MSE), and signal to noise ratio (SNR) are 23.86, 1.405, 2.55, 19.08, 0.999, 0.12, 0.054 and 37.611 dB, respectively. The proposed 8-channel uniform filter bank is used to detect the R-peak locations of the ECG signal. The comparative analysis shows that beats (locations and amplitudes) of both signals (original and reconstructed signals) are same.

Süzgeç Bankası Tasarımında Kullanılan ABC Algoritmasının Kontrol Parametrelerindeki Değişimin Performansa Etkisinin İncelenmesi

In this work, Cosine Modulated Filter Bank (CMFB) is designed using Artificial Bee Colony (ABC) Algorithm. In heuristic algorithms, one of the important factors affecting the performance of the algorithm is to determine the control parameters of the algorithm. The performance of the designed filter bank is investigated according to the change in the control parameters of the ABC Algorithm. The effects on the filter bank performance parameters of the change in the control parameters are detailed.

Design of Low-redundant Cosine-modulated Nonuniform Filter Bank with Flexible Frequency Division

In this paper, a low-redundant cosine-modulated nonuniform filter bank (LR-CMNFB) and its design method are proposed. The proposed LR-CMNFB consists of two parallel subsystems which have the same frequency division scheme. The nonuniform analysis and synthesis filters of the first subsystem are formed by directly merging the consecutive cosine-modulated versions of a lowpass prototype filter, and the filters of the second subsystem are derived to meet the aliasing cancelation condition. Since the aliasing of the two subsystems is structurally canceled without guardband constraint on the filter location, the shift-invariance and flexible nonuniform frequency division, two important properties in many signal and image processing applications, can be achieved simultaneously at the cost of low redundancy (that is less than 2). From a particular analysis on the filter characteristic and the reconstruction error of the whole system, it is found that the good characteristics of filters and the good reconstruction performance of LR-CMNFB can be jointly obtained by constraining the prototype filter to be the linear-phase spectral factor of a 2 Mth band filter. Several design examples are given to illustrate the performance of the proposed LR-CMNFB and its potential in practical applications.

A Novel Design of Sparse Prototype Filter for Nearly Perfect Reconstruction Cosine-Modulated Filter Banks

Cosine-modulated filter banks play a major role in digital signal processing. Sparse FIR filter banks have lower implementation complexity than full filter banks, while keeping a good performance level. This paper presents a fast design paradigm for sparse nearly perfect-reconstruction (NPR) cosine-modulated filter banks. First, an approximation function is introduced to reduce the non-convex quadratically constrained optimization problem to a linearly constrained optimization problem. Then, the desired sparse linear phase FIR prototype filter is derived through the orthogonal matching pursuit (OMP) performed under the weighted l 2 norm. The simulation results demonstrate that the proposed scheme is an effective paradigm to design sparse NPR cosine-modulated filter banks.

Optimal design of finite precision and infinite precision non-uniform cosine modulated filter bank

This paper investigates the design of non-uniform cosine modulated filter bank (CMFB) with both finite precision coefficients and infinite precision coefficients. The finite precision filter bank has been designed to reduce the computational complexity related to the multiplication operations in the filter bank. Here, non-uniform filter bank (NUFB) is obtained by merging the appropriate filters of an uniform filter bank. An efficient optimization approach is developed for the design of non-uniform CMFB with infinite precision coefficients. A new procedure based on the discrete filled function is then developed to design the filter bank prototype filter with finite precision coefficients. Design examples demonstrate that the designed filter banks with both infinite precision coefficients and finite precision coefficients have low distortion and better performance when compared with other existing methods.

Design of the Multi-Channel Cosine-Modulated Filter Bank Using the Bacterial Foraging Optimization Algorithm

ABSTRACTThe design of a multi-channel cosine-modulated filter bank (CMFB) using bacterial foraging optimization (BFO) is proposed. In this work, the canonic signed digit (CSD) technique is used to optimize the filter coefficients. At pass-band frequency, the magnitude response of the proposed filter bank is near to that of a perfect filter. The performance of the proposed BFO scheme is evaluated and compared with that of the reported modified cuckoo search (MCS) and artificial bee colony modified rate (ABC-MR) algorithms for design of the CMFB using different windows. Our simulation results reveal that a reduction up to 88% and 90% can be achieved in average amplitude distortion and average aliasing distortion, respectively, with 22% reduction in computation time using the proposed BFO algorithm when compared with the MCS technique. The proposed BFO algorithm is a more efficient technique for reconstruction of original signals with minimum computation time.

A review on the cosine modulated filter bank studies using meta-heuristic optimization algorithms

There has been a significant increase in the number of designs based on optimization techniques as the usage areas of computers have increased day by day. In this paper, Cosine Modulated Filter Banks (CMFBs) using meta-heuristic optimization techniques are reviewed. The basic features of the meta-heuristic optimization algorithms which used in related studies and the purpose of these algorithms in CMFB design are explored. The paper begins with a definition of CMFBs and continues with meta-heuristic algorithms used in CMFB studies. Later, the meta-heuristic algorithms used to design the CMFBs are briefly described. Finally, it is reviewed where algorithms are used in the CMFB designs. This study aims to clarify the role of meta-heuristic algorithms in CMFB design. The main contribution of the study to the literature is not just describing meta-heuristic algorithms, the proposed methods in the literature to design the CMFB are fully described and compared.

Multichannel loudness compensation method based on segmented sound pressure level for digital hearing aids

To improve the performance of gain compensation based on three-segment sound pressure level (SPL) in hearing aids, an improved multichannel loudness compensation method based on eight-segment SPL was proposed. Firstly, the uniform cosine modulated filter bank was designed. Then, the adjacent channels which have low or gradual slopes were adaptively merged to obtain the corresponding non-uniform cosine modulated filter according to the audiogram of hearing impaired persons. Secondly, the input speech was decomposed into sub-band signals and the SPL of every sub-band signal was computed. Meanwhile, the audible SPL range from 0 dB SPL to 120 dB SPL was equally divided into eight segments. Based on these segments, a different prescription formula was designed to compute more detailed gain to compensate according to the audiogram and the computed SPL. Finally, the enhanced signal was synthesized. Objective experiments showed the decomposed signals after cosine modulated filter bank have little distortion. Objective experiments showed that the hearing aids speech perception index (HASPI) and hearing aids speech quality index (HASQI) increased 0.083 and 0.082 on average, respectively. Subjective experiments showed the proposed algorithm can effectively improve the speech recognition of six hearing impaired persons.

Design perfect reconstruction cosine-modulated filter banks via quadratically constrained quadratic programming and least squares optimization

In this paper, the design of perfect reconstruction (PR) cosine-modulated filter banks (CMFBs) is implemented via quadratically constrained quadratic programming (QCQP) and least squares (LS) optimization. To this end, a PR CMFB design problem is formulated as a nonconvex QCQP after re-arranging the coefficients of the prototype filter. Then a deep insight is offered into the algebraic relationship between the PR conditions and near-perfect reconstruction (NPR) ones for CMFB designs. Here we theoretically show that the NPR conditions are just the summations of the PR conditions. Firmly in the light of this relationship, a two-stage method is proposed for PR CMFB design. We firstly solve an NPR CMFB problem to obtain its optimal solution as a reference point, then model the PR CMFB design problem as a series of small-sized LS problems near the reference point. And we solve the LS problems in parallel with cheap iteration. Our analysis and numerical results show that the proposed method bears superior performance on effectiveness and efficiency, especially in the case of designing PR CMFBs with large number of channels.

The Subwoofer Room Impulse Response (SUBRIR) Database

This report introduces a new database of room impulse responses (RIRs) measured in an empty rectangular room using subwoofers as sound sources. The purpose of this database, publicly available for download, is to provide acoustic measurements within the frequency region of modal resonances. Performing acoustic measurements at low frequencies presents many difficulties, mainly related to ambient noise and to unavoidable nonlinearities of the subwoofer. In this report, it is shown that these issues can be addressed and partially solved by means of the exponential sine-sweep technique and a careful calibration of the measurement equipment. A procedure for estimating the reverberation time at very low frequencies is proposed, which uses a cosine-modulated filterbank and an approximation of the RIRs using parametric models in order to reduce problems related to low signal-to-noise ratio and to the length of typical band-pass filter responses.

Spectral detection with multistage granularity bands using filter bank techniques for CR applications

In this paper, we propose a method to detect unused spectrum using multistage Cosine Modulated Filter Bank (CMFB) technique for Cognitive Radio (CR) applications. The precision of spectral detection is increased when the number of sub-bands in the filter bank is increased, this increases the computational complexity of the filter bank structure. We suggest a multistage filter bank structure to reduce the computational complexity. Spectrum detection is done effectively in filter banks by proper choice of prototype filter with specified sub-band attenuation. The sub-bands detected in coarser granularity bands are sensed with finer granularity bands for precise spectral detection depending on the predefined threshold and probability of false alarm. The remaining sub-bands are not sensed further which in turn reduces the computational complexity. Through simulations it is shown that spectrum detection with multistage granularity bands maintains bandwidth efficiency and reliability in spectrum detection even at low SNR.