Half-band Filters Research Articles

A Σ-Δ ADC with a DPOQ system and a new multi-Stage digital filter

This paper proposes a high-precision Sigma Delta ADC for automotive electronic sensors and delves into methods for optimizing quantizers and filters, with a focus on DPOQ quantizers and hybrid CIC filters. This ADC features a Dual-path One-bit Quantization (DPOQ) System, which improves the accuracy of Sigma-Delta ADCs while reducing hardware consumption. Meanwhile, this paper presents a new multistage digital filter. The filter uses a cascade of multiple filters, including cosine-like (CL), cascaded integral comb (CIC), interpolated second-order polynomial (ISOP), and half-band (HB) filters, to enhance the ADC’s accuracy. The filter are designed using canonical signed digit (CSD) and common subexpression (CSE) optimized the design algorithm of the filter, to reduce hardware resource consumption and improve computational performance. The ADC is synthesized using 180 nm CMOS technology, achieving an output SNDR of 96.26 dB, ENOB of 15.73 bits, and total power of 518.35 uW.

A novel optimal wavelet filter banks for automated diagnosis of Alzheimer’s disease and mild cognitive impairment using Electroencephalogram signals

Electroencephalogram (EEG) of Alzheimer’s disease (AD) patients show a slowing effect and less synchronization. EEG signal’s transient and abrupt nature is captured from various mother wavelets. However, better performance can be obtained by balancing time–frequency localization in wavelet filters. We propose a new approach for designing filter banks based on optimal time–frequency localization of a four-step lifting structure (FSLS). First, we design a FSLS using Euler’s Frobenius half-band polynomial (EFHBP). The perfect reconstruction condition and vanishing moments are imposed on EFHBP to achieve maximum flat half-band filters (HBFs). HBFs are optimized using a balanced uncertainty metric to obtain a time–frequency spread balance. Afterward, these HBFs are used in the FSLS to obtain the synthesis and analysis filter banks. The proposed time–frequency optimized biorthogonal wavelet filter banks (TFOBWFBs) achieved a balance between time–frequency localization. Further, these TFOBWFBs are applied to decompose the EEG signals of AD patients. Twenty different features were extracted from decomposed EEG subbands, of which twelve significant features were selected using Kruskal Walli’s test. The machine learning models were trained and tested using obtained features with 10-fold cross-validation and leave-one-subject-out cross-validation. To validate this study, the proposed TFOBWFBs have been applied to two publicly available EEG datasets of mild cognitive impairment (MCI), AD, and healthy control (HC) subjects. The proposed TFOBWFBs achieved 98.90% accuracy for 2-way (AD vs. HC) and 96.50% for 3-way (AD vs. MCI vs. HC) classification using a support vector machine model with a 10-fold cross-validation. The proposed method outperforms the existing AD and MCI detection techniques. The performance of the proposed machine learning framework with optimization of wavelet filter banks is more significant and fast compared to previous studies. Also, the proposed framework can be applied to detect other neurodegenerative disorders.

Recursive digital filters with optimum equiripple passband magnitude characteristic

The paper investigates, for the first time, the design of recursive digital filters that exhibit optimum equiripple passband magnitude characteristics. After a brief description of the optimum equiripple filters in the analog domain, digital optimum C (Chebyshev) tan and sine filters are derived directly in the digital domain through the minimization of the area under the passband characteristic function. The influence of the truncated coefficients is also considered and its effects are demonstrated through an example proving the robustness of the magnitude function. Furthermore, a design procedure is proposed for the optimum C tan half-band filter. To highlight the effectiveness of the proposed approximation, a comparative analysis is conducted with the staircase digital filter, as both filters optimize passband responses by minimizing the area under the characteristic function. The results of comparison demonstrate that the optimum equiripple approximation surpasses the staircase approximation, not only in the analog but also in the digital domain.

Research on onboard multistage digital demultiplexer for satellite communication based on MF-TDMA system

A new multicarrier multi-rate digital demultiplexer system structure based on MF-TDMA(Multi-Frequency Time Division Multiple Access) in a wideband satellite communication system is described. Compared with the traditional tree multicarrier demultiplexer method, the new structure uses a half-band filter instead of the quadrature mirror filter, which has three advantages: 1) It fully avoids the shortcomings of the traditional method, such as confusion distortion and amplitude distortion. 2) The computation to achieve filtering is reduced by nearly half. 3) It effectively improves the demodulation performance of the system. In this paper, the new structure performs the multistage digital demultiplexer and demodulation of the MF-TDMA signal. The results show no obvious signal distortion, which is demultiplexed by the new structure. The bit error rate of the demodulated signal is better than that of the traditional single carrier demodulator. The bit error rate is very close to the theoretical value of QPSK demodulation.

Design and Implementation of High Speed Low Power Decimation Filter for Hearing AID Applications

This work is focused on designing and implementing a decimation filter specifically intended for use in hearing aid applications. The filter utilizes distributed arithmetic (DA) and is described in this brief. Our proposal involves the development of a reconfigurable finite impulse response (FIR) filter, which utilizes both offset binary code (OBC) and binary distributed arithmetic (DA) techniques. Additionally, we utilize canonic signed digit (CSD) representation to develop decimation filters, which include the CIC filter, half band filter, and corrector filter. In this work, we have implemented a decimation filter using Matlab Simulink. We have utilized Xilinx Vivado 19.2 to execute the FIR filters, binary DA filters, and OBC DA-based filters. Our focus is on implementing these filters using VLSI architecture, in order to achieve low power consumption, reduced latency, less area, and fast speed.

Hardware Efficient Reconfigurable Digital Down Converter for Software Radio Receiver

ABSTRACT This paper describes a reconfigurable digital down converter (DDC) that can reduce the input sampling frequency from 128 MHz to an output of 1 MHz on a field-programmable gate array (FPGA) device. The proposed design employs a polyphase mixer followed by a half-band (HB) filter and a finite impulse response (FIR) filter. All the decimation filters involve polyphase architectures, enabling efficient hardware implementation. The polyphase mixer can reduce the high sampling rate frequency, and combining both HB and FIR filters results in a complex down-converted baseband spectrum. In addition, the modified HB filter reduces multiplier units, and the proposed FIR filter saves the delay elements. Using the optimal hardware description language (HDL) programming style, the design can further improve the area efficiency without sacrificing functionality. To evaluate the performance, the design has been implemented on the Kintex-7 Xilinx FPGA device. Experimental outcomes show that the proposed design significantly reduces hardware costs associated with other existing designs. Finally, a verification test certifies that the DDC has achieved a satisfactory spurious-free dynamic range (SFDR) of 115 dB. The high sampling rate and parallel processing capabilities of the proposed DDC make it an attractive solution for any software radio standard.

Conjugate complex function coupling strategy of interferometric field: Synthetic-wavelength interferometric fringe extraction in simultaneous dual-wavelength interferometry

Simultaneous dual-wavelength interferometry (SDWI) supplies a better solution to extend the measurement range of traditional single-wavelength interferometry with higher efficiency. To decompose the needed longer beat-frequency synthetic-wavelength (λS) information from the generated moiré fringe pattern in SDWI, a conjugate complex function coupling strategy (CCFC) of interferometric field is proposed in this study. By the Fourier transform and the half-band filter in one side of the spectrum, the positive half spectrum is obtained. The inverse Fourier transform and conjugate operation are performed on the half spectrums to obtain the two conjugate complex functions of the interferometric field. Coupled by the multiplication for the conjugate complex functions, the lower beat-frequency synthetic-wavelength interferometric fringe pattern is derived directly. And if the SDWI is implemented with the π/2 phase shift at λS, the obtained phase-shift interferogram for λS could be demodulated by the conventional phase-shift algorithm. Compared with other spatial-domain Fourier transform demodulation theory, the half-band filter used in CCFC method is appropriate for the different spectral width and carrier spatial frequency. The necessary introduced linear carrier is merely about 0.0947 times of the carrier in the former numerically. And it is only used to pursue the separation between the ±1 order phase lobes instead of the separation between the different wavelength phase lobes. The feasibility and applicability of the CCFC method are verified using simulation and experimental results.

Design and Implementation of Sigma-Delta ADC Filter

This paper presents a digital decimation filter based on a third-order four-bit Sigma-Delta modulator. The digital decimation filter is an important part of the Sigma-Delta ADC and is designed to make the Sigma-Delta ADC (Analog-to-Digital Converter) meets the requirements of Signal-to-Noise Ratio (SNR) not less than 120 dB and Equivalent Number of Bits (ENOB) not less than 20 bits. It adopts a three-stages cascaded structure including a Cascaded Integrator Comb (CIC) decimation filter, a Finite Impulse Response (FIR) compensation filter, and a half-band (HB) filter. This structure effectively reduces about 13% multiplier cells and memory cells. The coefficient symmetry technique and CSD (Canonic Signed Digit) coding technique are used to optimize the parameters of the filter, which further reduces the computational complexity. After optimization, the circuit area is reduced by about 15%, and the logic resources are decreased by about 23%. The Verilog hardware description language is used to describe the behavior of the digital decimation filter, and the simulation is carried out based on the VCS (Verilog Compile Simulator) platform. At the same time, the prototype verification is implemented on the Xilinx Artix-7 series FPGA, and the ADC achieves 113 dB SNR and 18.5 bits ENOB. Finally, the Sigma-Delta ADC is fabricated on SMIC 0.18 μm CMOS process with the layout area of 714.8 μm × 628.4 μm and the power consumption of 11.2 mW. The more tests for the fabricated prototypes will be performed in the future to verify that the Sigma-Delta ADC complies with the design specifications.

Reconstruction of an Image Based on 13/19 Triplet Half-Band Wavelet Filter Bank and Orthogonal Matching Pursuit

Compressive Sensing Scheme for image reconstruction presented in this paper is depending on a combination of Orthogonal Matching Search and a 13/19 triplet half band filter bank (THFB) which is resulting from 1/2-band polynomial. Here, the consideration is made for 13/19 triplet half band wavelet filter sets. The half-band polynomial is applied which is generalized and used to receive the required frequency response. The image reconstruction is done later based on this. The designed triplet wavelet filters give a sparse image which is used for the input image. Gaussian probability density function and the Orthogonal Matching Pursuit (OMP) are presented for reconstructing the image. The results and observations demonstrate that the compressive sensing by using OMP and designed wavelet filters offers good result for performance as compared to the existing wavelet filters.

A Flexible and Simple Lossless DWT Filter Bank Using a MAXFLAT FIR Half-Band Filter

This paper describes a simple, lossless and computationally efficient two-band single (s-) filter bank that creates an opposite band output by subtracting the primary filtered data from the original data. For computationally efficient and error-free s-filter bank achievement, a maximally flat (MAXFLAT) half-band filter with zero odd-order coefficients is characterized from a unique perfect reconstruction condition, and an explicit impulse–response formula (for non-zero integer coefficients of even order) is derived in a closed form of the filter. The examples are shown to provide a complete and accurate solution for the design of such s-filter banks. In addition, the effectiveness of the proposed s-filter banks is clearly verified by comparing the lossless 5/3 and lossy 9/7 filter banks (in the JPEG2000). The simulation results show that the s-filter banks lead to better performance than the JPEG2000 filter banks using two filters although allowing low computational complexity of less than 50%. This new approach is shown to provide significant advantages over existing lossless discrete wavelet transform (DWT) filter banks in both design flexibility and computational complexity.

Heuristic Analysis of Multiplierless Desensitized Half-Band Decimation Filter for Wireless Applications

This paper elucidates the half-band FIR filter, which plays an important role when applying decimation by a factor of two. When the down-conversion is applied in sampling rate, this digital filter is frequently employed in conjunction with down-samplers. Despite the fact that numerous approaches have been proposed for designing half-band FIR filters, this paper proposes an utterly unique method for designing and implementing multiplierless half-band FIR filters, which minimizes the coefficient sensitivity and also reduces hardware complexity of the conventional half-band FIR filter. The proposed desensitized and further desensitized multiplierless half-band FIR filters are analyzed with four high-speed parallel prefix adders in Xilinx Vivado development tool and built on Kintex 7 FPGA for exploring power consumption, number of LUTs and delay. The proposed half-band structure is compared with the classical half-band architecture with respect to power consumption, path delay and number of LUTs. Based on the attained results on Kintex 7 FPGA, the proposed low-sensitivity filter structure outperforms with a 41.09% reduction in the number of LUTs, a 11.91% reduction in delay and a 38.35% reduction in power consumption in contrast to the existing desensitized half-band filter. Subsequently, the proposed further desensitized filter provides a 4.87% reduction in stopband ripple than the desensitized structure and an 8.84% reduction than the existing half-band decimation filter.

Optimized hybrid machine learning approach for smartphone based diabetic retinopathy detection.

Diabetic Retinopathy (DR) is defined as the Diabetes Mellitus difficulty that harms the blood vessels in the retina. It is also known as a silent disease and cause mild vision issues or no symptoms. In order to enhance the chances of effective treatment, yearly eye tests are vital for premature discovery. Hence, it uses fundus cameras for capturing retinal images, but due to its size and cost, it is a troublesome for extensive screening. Therefore, the smartphones are utilized for scheming low-power, small-sized, and reasonable retinal imaging schemes to activate automated DR detection and DR screening. In this article, the new DIY (do it yourself) smartphone enabled camera is used for smartphone based DR detection. Initially, the preprocessing like green channel transformation and CLAHE (Contrast Limited Adaptive Histogram Equalization) are performed. Further, the segmentation process starts with optic disc segmentation by WT (watershed transform) and abnormality segmentation (Exudates, microaneurysms, haemorrhages, and IRMA) by Triplet half band filter bank (THFB). Then the different features are extracted by Haralick and ADTCWT (Anisotropic Dual Tree Complex Wavelet Transform) methods. Using life choice-based optimizer (LCBO) algorithm, the optimal features are chosen from the mined features. Then the selected features are applied to the optimized hybrid ML (machine learning) classifier with the combination of NN and DCNN (Deep Convolutional Neural Network) in which the SSD (Social Ski-Driver) is utilized for the best weight values of hybrid classifier to categorize the severity level as mild DR, severe DR, normal, moderate DR, and Proliferative DR. The proposed work is simulated in python environment and to test the efficiency of the proposed scheme the datasets like APTOS-2019-Blindness-Detection, and EyePacs are used. The model has been evaluated using different performance metrics. The simulation results verified that the suggested scheme is provides well accuracy for each dataset than other current approaches.

Minimax Design of 2D FIR Half-Band Filters Using an Efficient Matrix-Based IRLS Algorithm

This paper considers the minimax design of two-dimensional (2D) finite impulse response (FIR) half-band filters. First, the design problem is formulated in a matrix form, where the half-band constraints are expressed as a pair of matrix equations. By matrix transformations, the constrained minimax problem is transformed into an unconstrained one. Then, we propose an efficient iterative reweighted least squares (IRLS) algorithm to solve this problem. The weighted least squares (WLS) subproblems arising from the IRLS algorithm are solved using a generalized conjugate gradient (GCG) algorithm. Moreover, the GCG algorithm is guaranteed to converge in a finite number of iterations. In the proposed algorithm, the design coefficients of filters are solved in their matrix form, leading to a great saving in computations and memory space. Design examples and comparisons with existing methods are provided to demonstrate the effectiveness and efficiency of the proposed algorithm.

Automated Identification of Sleep Disorder Types Using Triplet Half-Band Filter and Ensemble Machine Learning Techniques with EEG Signals

A sleep disorder is a medical condition that affects an individual’s regular sleeping pattern and routine, hence negatively affecting the individual’s health. The traditional procedures of identifying sleep disorders by clinicians involve questionnaires and polysomnography (PSG), which are subjective, time-consuming, and inconvenient. Hence, an automated sleep disorder identification is required to overcome these limitations. In the proposed study, we have proposed a method using electroencephalogram (EEG) signals for the automated identification of six sleep disorders, namely insomnia, nocturnal frontal lobe epilepsy (NFLE), narcolepsy, rapid eye movement behavior disorder (RBD), periodic leg movement disorder (PLM), and sleep-disordered breathing (SDB). To the best of our belief, this is one of the first studies ever undertaken to identify sleep disorders using EEG signals employing cyclic alternating pattern (CAP) sleep database. After sleep-scoring EEG epochs, we have created eight different data subsets of EEG epochs to develop the proposed model. A novel optimal triplet half-band filter bank (THFB) is used to obtain the subbands of EEG signals. We have extracted Hjorth parameters from subbands of EEG epochs. The selected features are fed to various supervised machine learning algorithms for the automated classification of sleep disorders. Our proposed system has obtained the highest accuracy of 99.2%, 98.2%, 96.2%, 98.3%, 98.8%, and 98.8% for insomnia, narcolepsy, NFLE, PLM, RBD, and SDB classes against normal healthy subjects, respectively, applying ensemble boosted trees classifier. As a result, we have attained the highest accuracy of 91.3% to identify the type of sleep disorder. The proposed method is simple, fast, efficient, and may reduce the challenges faced by medical practitioners during the diagnosis of various sleep disorders accurately in less time at sleep clinics and homes.

Design of FIR Half-Band Filter With Controllable Transition-Band Steepness

Maximally flat (MAXFLAT) half-band filters usually have wider transition-band than other filters although the frequency response is maximally flat (i.e., no ripples) in the passband and stopband. This is due to fact that the maximum possible number of zeros at z = ±1 is imposed in half-band close form solution, which leaves no degree of freedom, and thus no independent parameters for direct control of the frequency response. This paper describes a novel method for the design of FIR half-band filters with an explicit control of the transition bandwidth. The proposed method is based on a generalized Lagrange half-band polynomial ( $g$ -LHBP) with coefficients parameterizing a 0 -th coefficient $h_{0}$ and allows the frequency response of this filter type to be controllable by adjusting $h_{0}$ . Then, $h_{0}$ is modeled as a steepness parameter of the transition-band and this is accomplished through theoretically analyzing a polynomial recurrence relation of the $g$ -LHBP. This method also provides explicit formulas for direct computation of design parameters related to choosing a desired filter characteristic (by a reasonable trade-off between the transition-band sharpness and passband & stopband flatness). The examples are shown to provide a complete and accurate solution for the design of such filters with relatively sharper transition-band steepness than other existing half-band filters.

Low Power Structure Digital Up Converter Design for Software Radio System

The numerically controlled oscillator is often supposed to operate after interpolation in a conventional digital up converter, but such a converter works at quite high frequencies and consumes more power. In this paper, a type of low power structure digital up converter is proposed which carries out mixing and interpolating gradually, where the numerically controlled oscillator and the interpolation filter can both work at a lower frequency. Low power structure can move signal to any position within the whole Nyquist Band. Furthermore, the interpolation filter adopts a half-band filter with the structure of two parallel branches, which combines the functions of stuffing zero, filtering and modulation, and makes programmable modulation by exchanging input paths. A simulation is carried out on the Xilinx KC705 development kit, which indicates that its maximum work frequency of the low power structure reaches 392[Formula: see text]MHz while its power consumption reduces by 33.3% compared to the conventional structure.

A Non-Adaptive Single-Phase PLL Based on Discrete Half-Band Filtering to Suppress Severe Frequency Disturbances

The interconnection of new generating and storing devices to the power grid imposes the necessity of synchronizing, so the power flow can be manipulated and distributed. In the presence of an increasingly perturbed electric grid, many proposals of novel and modified synchronization techniques attained enough robustness to deal with known perturbations. However, such proposals exhibit drawbacks on their own, leaving open enhancement opportunities, mostly over their discrete implementation—e.g., sampling issues and not-considered inter/harmonics—and their inherent complexity—e.g., the need for frequency adaptability. In this work, three traditional synchronous reference frame (SRF) phase-locked loops (PLL) are modified to implement discrete filtering, such as the well-known proposals based on moving average filters (MAFs), to avoid the problems mentioned above, known for affecting the MAF’s performance. This proposal makes use of discrete, efficient units modularly assembled to yield a signal’s average, based on elliptic half-band filters. The proposed PLLs were tested and exhibited clear advantages—robustness against frequency disturbances—over MAF-based equivalents at standardized tests over a typical simulation environment, setting through this work an initial milestone for its verification and further incorporation in more complex synchronization topologies.

Cryptographic Algorithm based Feature Level Fusion of Fingerprint and Iris in a Multi-Biometric Recognition System

Biometric encryption is one of the developing exploration area, which is a strategy for merging biometric features with cryptographic keys. Biometric Recognition is based on the anatomical and behavior attributes of the individuals. Multibiometric is the combination of various biometrics like Fingerprint, Iris, and Face, Fingervein etc. Experts are concentrating on the most proficient method to give security to the framework, the template which was produced from the biometric should be ensured. The main objective of this paper is to protect the multi biometric template by creating a protected sketch by deploying bio cryptosystem. Once the biometric template is stolen it turns into a major issue for the security of the framework and furthermore for client protection. In this way, a bio-crypto framework ensures the confidentiality of the information. In this paper bio cryptosystem is proposed to improve the security of multimodal frameworks by producing the biocrypto key from Finger print and iris. Gray level co-occurrence matrix (GLCM) based Haralick features, local binary pattern (LBP), triplet half-band filter bank (THFB) and dynamic features (DF) are extracted from fingerprint and iris. The high dimensionality space of the features are reduced using kernel principal component analysis (KPCA. Finally, the encoding process is matted with biometric key utilizing symmetric RSA (Rivest-Shamir-Adleman) cryptographic algorithm.

Efficient Rationalization of Triplet Halfband Filter Banks and its Application to Image Compression

This paper presents a novel approach for rationalization of irrational coefficients of filters designed using three-step lifting scheme. The existing three-step lifting schemes result in the irrational filter coefficients which require infinite precision for implementation. In this work, Euler-Frobenius halfband polynomials are designed to obtain the required kernels of three-step lifting structure. Next, the efficient rationalization of the designed filter banks (FBs) is proposed to reduce the arithmetic complexity. The proposed rational FBs preserve perfect reconstruction, near-orthogonality and regularity properties of wavelet FBs. These filters with rational coefficients are then used in image compression algorithms to compress the test images in well-known Classic, EPFL, RAISE, FiveK datasets and chromosome image datasets. The performance of the proposed rational FBs is compared with the existing rational FBs. It is observed that the performance of the proposed rational FBs is improved in terms of computational cost, encoding-decoding time and compression ratio as compared to existing rational FBs.

Design of High-Speed Desensitized FIR Filter Employing Reduced Complexity SQRT Carry Select Adder

In this research, a highly efficient desensitized FIR filter is designed to enhance the performance of digital filtering operation. With regard to FIR filter design, Multiplication and Accumulation component (MAC) forms the core processing entity. Half-band filters employing Ripple Carry Adder (RCA) based MAC structures have a sizeable number of logical elements, leading to high delay and high power consumption. To minimize these issues, a modified Booth multiplier encompassing SQRT Carry Select Adder (CSLA) based MAC component is proposed for the desensitized filter with reduced coefficients and employing lesser number of logical elements forgiving optimum performance with respect to delay and power consumption. The suggested FIR filter is simulated and assessed using EDA simulation tools from Modelsim 6.3c and Xilinx ISE. The results obtained from the proposed Desensitized FIR filter employing the modified booth multiplier with reduced complexity based SQRT CSLA show encouraging signs with respect to 12.08% reduction in delay and 2.2% reduction in power consumption when compared with traditional RCA based digital FIR filter.