Finite Impulse Response Digital Filters Research Articles

FPGA implantations of TRNG architecture using ADPLL based on FIR filter as a loop filter

This article describes about the design, implementation, and analysis of a true random number generator (TRNG) employing an all-digital phase-locked loop (ADPLL) based on a finite impulse response (FIR) filter as the digital loop filter and implemented on the Artix 7(XC7A35T-CPG236-1) field programmable gate array (FPGA) board using the Xilinx Vivado v.2015.2 design suite. The coefficients of a 3rd-order broadcast low-pass digital FIR filter are computed using the Keiser window method. The MATLAB-FDA tool is used to calculate the filter coefficient. After reducing the bias in the sequence using the XOR-corrector post-processing approach, the suggested ADPLL-based TRNG designs created an unbiased stochastic random number with an overall throughput of 200 Mbps for both designs. The first proposed FIR-ADPLL-based TRNG design (FAT-1) consumes 0.072 W of power, whereas the second proposed FIR-ADPLL-based TRNG design (FAT-2) consumes 0.074 W. The resulting bitstream is verified for randomness using national institute of standards and technology (NIST) test following post-processing. Digital storage oscilloscope (DSO) is interfaced to the Artrix-7 FPGA board in order to capture the TRNG output waveforms. Both the proposed FIR-based ADPLL-TRNG designs passed the NIST SP 800-22 test, indicating that they are well-suited for a variety of industrial applications, including network security, cybersecurity, banking security, smart cards, radio-frequency identification tags, Internet of Things, and Industrial Internet of Things.

Knowledge-driven feature component interpretable network for motor imagery classification

Objective. The end-to-end convolutional neural network (CNN) has achieved great success in motor imagery (MI) classification without a manual feature design. However, all the existing deep network solutions are purely datadriven and lack interpretability, which makes it impossible to discover insightful knowledge from the learned features, not to mention to design specific network structures. The heavy computational cost of CNN also makes it challenging for real-time application along with high classification performance. Approach. To address these problems, a novel knowledge-driven feature component interpretable network (KFCNet) is proposed, which combines spatial and temporal convolution in analogy to independent component analysis and a power spectrum pipeline. Prior frequency band knowledge of sensory-motor rhythms has been formulated as band-pass linear-phase digital finite impulse response filters to initialize the temporal convolution kernels to enable the knowledge-driven mechanism. To avoid signal distortion and achieve a linear phase and unimodality of filters, a symmetry loss is proposed, which is used in combination with the cross-entropy classification loss for training. Besides the general prior knowledge, subject-specific time-frequency property of event-related desynchronization and synchronization has been employed to construct and initialize the network with significantly fewer parameters. Main results. Comparison of experiments on two public datasets has been performed. Interpretable feature components could be observed in the trained model. The physically meaningful observation could efficiently assist the design of the network structure. Excellent classification performance on MI has been obtained. Significance. The performance of KFCNet is comparable to the state-of-the-art methods but with much fewer parameters and makes real-time applications possible.

Flexible Sub-bands F-OFDM Configured for Spectrum Efficiency Enhancement in 5G System

The new product of wireless communication systems, the Fifth generation (5G), promises higher data rates and Spectrum Efficiency (SE) enhancements to support the communication of heterogeneous services. The Filtered-OFDM (F-OFDM) technique was proposed as the strongest candidate waveform for the physical layer in 5G to fulfill these requirements. In F-OFDM, the whole band is split into narrow sub-bands, each filtered by a digital Finite Impulse Response (FIR) filter with different specifications to increase the spectrum utilization and allow for asynchronous transmission. This paper proposes a novel F-OFDM design waveform for the first time with four sub-bands in equal and unequal sub-band sizes of seven kinds of window sinc filters and a variety of numerology designs to observe SE enhancement using Matlab-Simulink Software. Simulation results show that F-OFDM can reduce Out-Of-Band Emission (OOBE) and achieve SE of about (5%-6%) higher than conventional OFDM for equal and unequal sized sub-bands, respectively, by optimizing the guard band between the designed sub-bands, which achieves 5G guard band requirements.

Removing Powerline Interference from EEG Signal using Optimized FIR Filters

The Electroencephalography (EEG) is a signal representing the electrical activity of the brain and is used in the diagnosis of brain diseases. The EEG signal is weak and highly prone to noise from the powerline which generates a sinusoidal signal with the main frequency of 5060 Hz. Therefore, three harmonics of powerline noise must be removed using notch filters for a perfect diagnosis which requires three series notch filters. This paper presents a new method to design a digital notch finite impulse response (FIR) filter using a modified particle swarm optimization technique. The proposed method provides a short length, maximum stopband attenuation, and small transition width compared to different algorithms which results in removing the noise in EEG signal efficiently.

FPGA Design of a High- Resolution FIR Band-Pass Filter by Using LabVIEW Environment

Designers regularly use Finite Impulse Response (FIR) filters to fulfil the need for current electronic design applications such as signal or image processing and digital communications because of the remarkable selectivity computational efficiency. Fast and efficient information processing requires a dedicated microprocessor or a digital signal processor that may not always be available or provide enough performance. In such scenarios, designers can configure FPGAs for processing digitized signals. One of the most popular signal processing applications is filtering. Unlike the Infinite Impulse Response (IIR) filters, FIR filters do not have analog equivalent circuits. For this purpose, continuous time-discrete time conversion is not possible with the help of transforms. Because analog filters cannot have a finite impulse response, the design methods of FIR filters can be made as windowing method, pulse response truncation, and optimal filter design method. Considering this information, it aims to digitally separate two signals with different frequencies (2.4 kHz and 4.2 kHz), which are given to the input as analog, to obtain the desired information signal and suppress other signals. We preferred to use LabVIEW graphical programming language to get the digital FIR filter coefficients. We selected rectangular windowing, set the digital filter's sampling frequency as 18720 Hz, and determined the filter's coefficient with high-frequency resolution as 24. Using filter coefficients in the real-time FPGA-VHDL environment, we showed the performance and resource consumption. LabVIEW is used for simulation as well as obtaining filter coefficients. In addition, we compared both simulation and real-time FPGA-VHDL application output waveforms and examined both platforms' advantages and disadvantages.

Uniform rectangular distribution of far-field intensity by optical phased array

In this paper, to solve the problem of uneven distribution of far-field intensity of Flash Lidar, a method of amplitude modulation for optical phased array (OPA) is proposed, which makes the far-field intensity distribution close to the uniform rectangular distribution. We use the impulse response sequence of Finite Impulse Response (FIR) digital filter designed by the window functions to modulate the amplitude of the OPA. This kind of uniform intensity distribution can simultaneously detect a wide range with the same intensity. The modulation sequence can also be extended to two-dimensional situation. In the case of considering the radiation pattern of optical waveguide, the amplitude modulation sequence can also be modified to obtain the far-field pattern that is close to the uniform rectangular distribution.

Area-Delay-Power Efficient VLSI Architecture of FIR Filter for Processing Seismic Signal

Low-complexity, high-speed and re-configurability are the primary requirements of the finite impulse response (FIR) filters employed for the processing of acquired seismic signal in real-time seismic-alert-system. The common sub-expression elimination (CSE) technique is employed widely to reduce the hardware complexity by minimizing the logic operators (LOs) and logic depths (LDs) in digital FIR filter. In this brief, a novel matrix grouped CSE (MCSE) algorithm has been proposed which outperforms the existing CSE algorithms in terms of LOs and LDs minimization. Moreover, a new half-unit biased (HUB) based rounding technique is incorporated in the proposed design to reduce the truncation error while maintaining low-complexity and the cut-set retiming technique is employed to reduce the critical-path-delay (CPD). Two hardware efficient FIR filter architectures (I and II) involving the proposed canonical signed digit (CSD) based MCSE algorithm, HUB rounding and cut-set retiming approach have been presented. Further, the architecture II represents a hardware efficient realization of a reconfigurable FIR filter. The hardware implementation of the architectures is performed on both FPGA and ASIC platforms. The hardware implementation of the proposed architecture I yields more than 25%, 49%, 38%, 36% and, 31% reduction in LOs, CPD, effective latency, area-delay-product (ADP) and, power-delay-product (PDP), respectively, over the state-of-the-art CSE based architectures. Whereas the reconfigurable architecture II exhibits nearly 48%, 12% and, 13% reduction in CPD, ADP and, PDP over the counterpart.

LOW POWER VERY LARGE SCALE INTEGRATION (VLSI) DESIGN OF FINITE IMPULSE RESPONSE (FIR) FILTER FOR BIOMEDICAL IMAGING APPLICATION

Nowadays, the medical image processing techniques are using Very Large Scale Integrated (VLSI) designs for improving the availability and applicability. The digital filters are important module of Digital Signal Processing (DSP) based systems. Existing Finite Impulse Response (FIR) design approach performed with Partial Full Adder (PFA) based Carry Lookahead Adder (CLA) and parallel prefix adder logic in Vedic multiplier. Objective of this approach is to improve the performance of VLSI circuit by obtaining the result of area, power and delay, also, effective incorporation between VLSI circuit and image processing approach makes improved application availability. The design of high speed digital FIR filter is designed with various adders and multipliers. The incorporation of VLSI design and image processing techniques are used on biomedical imaging applications. The Enhanced FIR filter design utilized the hybrid adder and adaptive Vedic multiplier approaches for increasing the performance of VLSI part and the image processing results are taken from Matrix Laboratory tool. This proposed FIR filter design helps to perform the biomedical imaging techniques. The simulation result obtains the performance of enhanced FIR with area, delay and power; for biomedical imaging, Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) is obtained. Comparing with existing and proposed method, the proposed FIR filter for biomedical imaging application obtains the better result. Thus the design model states with various application availability of VLSI image processing approaches and it obtains the better performance results of both VLSI and image processing applications. Overall, the proposed system is designed by Xilinx ISE 14.5 and the synthesized result is done with ModelSim. Here the biomedical image performance is done by using MATLAB with the adaptation of 2018a. Keywords- Enhanced FIR filter; Adaptive vedic multiplier; Hybrid adder; Biomedical imaging; power delay product;

Determination of k-mer density in a DNA sequence and subsequent cluster formation algorithm based on the application of electronic filter

We describe a novel algorithm for information recovery from DNA sequences by using a digital filter. This work proposes a three-part algorithm to decide the k-mer or q-gram word density. Employing a finite impulse response digital filter, one can calculate the sequence's k-mer or q-gram word density. Further principal component analysis is used on word density distribution to analyze the dissimilarity between sequences. A dissimilarity matrix is thus formed and shows the appearance of cluster formation. This cluster formation is constructed based on the alignment-free sequence method. Furthermore, the clusters are used to build phylogenetic relations. The cluster algorithm is in good agreement with alignment-based algorithms. The present algorithm is simple and requires less time for computation than other currently available algorithms. We tested the algorithm using beta hemoglobin coding sequences (HBB) of 10 different species and 18 primate mitochondria genome (mtDNA) sequences.

Acoustic-pressure sensor array system for cardiac-sound acquisition

This paper presents a cardiac-sound-detection system based on an acoustic-pressure sensor array. The traditional cardiac-sound probe has the disadvantages of high cost and thick structure, which makes embedding difficult. Therefore, a methodology for cardiac-sound detection, comprising a sound-pressure sensor array, is proposed to achieve a low cost, very thin, and wearable cardiac-sound probe, which can be embedded in furniture or clothes for long-term heart sound monitoring. By introducing several miniature electret-condenser-microphone-based acoustic-pressure sensors, a sensor array for picking up cardiac sound was designed. The data-processing platform comprised a field-programmable gate array and microcontroller unit. Furthermore, a series of de-noising methods including oversampling, finite impulse response digital filtering, and digital extraction were used, thereby facilitating accurate cardiac-sound signal identification. Test results showed that the average Root Mean Square amplitude of the noise after processing was more than 3 dB lower than that of the signal obtained from a single sensor in the array. The signal-to-noise ratio improved more than 7 dB after processing. Furthermore, actual cardiac sounds were acquired and compared using the proposed sensor array and the dedicated cardiac-sound sensor. The proposed 4 mm thick sensor array could effectively acquire S1- and S2-segments of cardiac sound. The proposed system demonstrates the potential for use in the development of wearable cardiac-sound monitoring systems.

A BCS code in the f-OFDM system: a promising candidate for 5G wireless communication systems

Recently, a novel BCS code differing from conventional concatenated (RS/BCH) codes has been proposed for LTE system. It achieved a significant improvement in the LTE system performance better than single codes and familiar concatenated (RS/BCH) codes. However, LTE systems that primarily depend on orthogonal frequency-division multiplexing (OFDM), no longer meet the demand of wireless-communication systems and their high data-rate requirements because of the rapid growth in the service aspect of such systems. In addition to high out-of-band emission (OOBE) and big peak to average power ratio (PAPR) of OFDM, it doesn’t meet the demand of 5G diverse service scenarios. Meanwhile, filtered OFDM (f-OFDM) is considered a candidate technique for 5G wireless communication systems which have OFDM features as well low OOBE. However, a trade-off exists among reducing OOBE, bit error rate (BER) degradation, and high PAPR. In this work, the BCS code is proposed for f-OFDM to enhance its system performance, while a root-raised-cosine windowed finite impulse response (FIR) filter is selected in f-OFDM to reduce OOBE levels. Results show that in the BPSK and QPSK modulation schemes, f-OFDM achieves a low level of OOBE after using an FIR digital filter against a high level of OFDM. Meanwhile, the proposed system using the BCS code enables remarkable improvement in BER performance and helps reduce PAPR better than conventional OFDM systems. Therefore, considering these features, the proposed system using the BCS code can be presented as a candidate for 5G wireless-communication systems.

A non-intrusive approach for fault detection and diagnosis of water distribution systems based on image sensors, audio sensors and an inspection robot

Fault diagnosis is important to maintain the normal operation of air-conditioning systems, reduce the energy consumption in buildings, and increase the service life of air-conditioning system equipment. We present a novel approach for fault detection and diagnosis system that relies on image and audio sensors and relevant algorithms.This paper proposes a fault diagnosis algorithm based on a robot that can automatically capture audio and image signals from microphone arrays and cameras during inspection in a chiller room. It includes audio- and image-based fault diagnosis algorithms. The validity of the algorithm combined with sensors is verified using data from actual equipment in a chiller room.The audio-based algorithm, which can monitor the abnormal sound of pumps to detect faults, utilizes Fourier transform, a finite impulse response digital filter, and an autoregressive integrated moving average model. We analyze the frequency domain of the pump signal and set the appropriate threshold to monitor abnormal signals based on the fitted model. Meanwhile, the image-based algorithms are divided into three sections to achieve three functions: 1) an AlexNet convolutional neural network is modified to classify the images of the chiller room equipment obtained by the visible light camera; 2) image morphology methods and trigonometric functions are used to read the dials’ indicators acquired by the visible light camera; and 3) optical character recognition is used to obtain the highest temperature value in the infrared image of the pump captured by the infrared camera, which helps maintenance staff verify the operation of the pump and detect faults as soon as possible.These diagnostic algorithms are non-intrusive, low cost, and easy to deploy. Combined with real-time data collection from the sensors on the robot, the algorithms can effectively improve the intelligence of the equipment room and allocate human resources more reasonably.

M-ary phase-shift keying using finite impulse response filter based on window function method

Digital filters are vastly utilized in the area of communication. A perfect digital filter efficiency is significant and hence to design a digital finite impulse response filter (FIR) favorable all the wanted situations is necessary. In this paper, a new proposed FIR digital filter designed, the fineness of the submitted filter is tested in terms of BER and then matched with another window, namely Hamming, Hanning, and Blackman. The design procedure done in the MATLAB software. It is concluded that the Blackman window is the best window to design the FIR digital filter, because it is bit error rate is better than another window.

Uniform patterns based area-efficient and accurate stochastic computing finite impulse response filter.

Stochastic computing has recently gained attention due to its low hardware complexity and better fault tolerance against soft errors. However, stochastic computing based circuits suffer from different errors which affect the output accuracy of these circuits. In this paper, an accurate and area-efficient stochastic computing based digital finite impulse response filter is designed. In the proposed work, constant uniform patterns are used as stochastic numbers for the select lines of different MUXes in the filter and the error performance of filter is analysed. Based on the error performance, the combinations of these patterns are proposed for reducing the output error of stochastic computing based filters. The architectures for generating these uniform patterns are also proposed. Results show that the proposed design methodology has better error performance and comparable hardware complexity as compared to the state-of-the-art implementations.

Finite impulse response low-pass digital filter based on particle swarm optimisation for image denoising

Noise has very important influence on image quality. Finite Impulse Response (FIR) digital filter is an effective technique for removing image noise. The effectiveness of FIR digital filters designed by traditional methods in image denoising needs to be improved further because of their demerits such as lower accuracy. Therefore, to suppress noise and improve image quality, FIR low-pass digital filter designed by the improved particle swarm optimisation algorithm based on refraction principle (refrPSO) is employed. In the method, firstly, coefficients of FIR low-pass digital filter are mapped to a candidate solution of refrPSO, and then refrPSO is invoked to optimise it. Finally, the designed FIR low-pass digital filter is employed to denoise images. Experimental results of two images with different sizes show that the FIR digital filter designed by refrPSO has better image denoising effect compared with ones designed by window function method, best equivalent ripple approximation method, and PSO.

Windowing Techniques, the Welch Method for Improvement of Power Spectrum Estimation

This paper revisits the characteristics of windowing techniques with various window functions involved, and successively investigates spectral leakage mitigation utilizing the Welch method. The discrete Fourier transform (DFT) is ubiquitous in digital signal processing (DSP) for the spectrum analysis and can be efficiently realized by the fast Fourier transform (FFT). The sampling signal will result in distortion and thus may cause unpredictable spectral leakage in discrete spectrum when the DFT is employed. Windowing is implemented by multiplying the input signal with a window function and windowing amplitude modulates the input signal so that the spectral leakage is evened out. Therefore, windowing processing reduces the amplitude of the samples at the beginning and end of the window. In addition to selecting appropriate window functions, a pretreatment method, such as the Welch method, is effective to mitigate the spectral leakage. Due to the noise caused by imperfect, finite data, the noise reduction from Welch’s method is a desired treatment. The nonparametric Welch method is an improvement on the periodogram spectrum estimation method where the signal-to-noise ratio (SNR) is high and mitigates noise in the estimated power spectra in exchange for frequency resolution reduction. The periodogram technique based on Welch method is capable of providing good resolution if data length samples are appropriately selected. The design of finite impulse response (FIR) digital filter using the window technique is firstly addressed. The influence of various window functions on the Fourier transform spectrum of the signals is discussed. Comparison on spectral resolution based on the traditional power spectrum estimation and various window-function-based Welch power spectrum estimations is presented.

A novel technique for common sub-expression elimination for digital FIR filters using hit and miss transform

In this paper, a new design technique for hybrid common sub-expression elimination (CSE) algorithm is proposed based on Hit and Miss Transform (HMT). The novelty of proposed hybrid CSE is to exploit the basic concept of HMT for minimizing the common patterns, which is required in CSE, similar to minimization of structuring elements (SEs), performed as logic reduction of SEs through erosion process. This mechanism of logic reduction of HMT is imported as a new design technique in proposed hybrid CSE and has been examined through designing adder efficient multiplier-less finite impulse response (FIR) filters. The design results included in this paper illustrate the significance of proposed algorithm by achieving least number of adders in the realization.

WITHDRAWN: An Optimistic Design of 16-Tap FIR Filter with Radix-4 Booth Multiplier Using Improved Booth Recoding Algorithm

Abstract The digital Finite Impulse Response (FIR) is extensively used in numerous Signal Processing applications, ranging from wireless communication to video and image processing. The digital filter fundamentally consists of adder, multiplier and delay element. Multiplier is a vital and hard building block in FIR filter. Numerous methods have been described in the study to execute Field Programmable Gate Array (FPGA) in digital FIR filter. Due to conventional multiplier architectures more power exhaust in the existing FIR filter architecture. In the multiplier section partial product generation consume more power. In proposed work, the implementation of 16-Tap FIR Filter design is performed with Radix-4 Booth Multiplier using Improved Booth Recoding Algorithm. The proposed multiplier architecture helps to minimize the number steps in multiplication and also in digital circuits decrease the propagation delay. Finally getting better performance for area, delay and power consumption is applied in these architecture to the FIR filter. FPGA synthesis tools produces the implementation results based on that performance evaluation done. Compared to FIR filter with traditional multiplier, results clearly indicate that by using Radix-4 Booth Multiplier with Improved Booth Recoding Algorithm of FIR filter attains better performance in power, resource utilization and area. By employing Radix-4 Booth Multiplier using Improved Booth Recoding Algorithm in FIR filter, power and capacity is condensed by 52.27 % and 22.20% individually when compared to traditional FIR filter. The results show that the Improved Booth multiplier-based FIR (radix-4) filter leads to smallest power and area. For communication purpose, FIR filter is also applicable.

High performance hardware design of compressor adder in DA based FIR filters for hearing aids

Hearing aid is an acoustic device which is worn by hearing loss people. To compensate the different types of hearing loss, it is necessary to selectively amplify sounds at required frequencies. The main aim of the hearing aid is to selectively remove the noise signal such that the processed sound matches ones audiogram. To achieve this, the decimation filter in hearing aids can be design using multiplier less architecture which should be able to adjust sound levels at arbitrary frequencies within a given spectrum. In hearing aids, decimation filter plays a key role. This paper presents a low complexity design of a digital finite impulse response (FIR) filter for digital hearing aid application. This paper proposed approximate 4:2 compressor adders in memory less DA based FIR filter architecture. In DA architecture the area of the ROM increases gradually when filter order is increased. Memory less DA is designed using compressor adders is a solution to decrease the power consumption and area of the FIR filters and makes the area and power reduction for hearing aid application. The proposed DA based FIR filter architecture is synthesized on 90 nm technology using Synapsis Application Specific Integrated circuit design compiler. The proposed architecture has 45% reduction in area delay product when distinguish with systolic architecture and 10% less ADP when compare with OBC DA architecture. The proposed design is also implemented Field Programmable Gate Array and the results shows that the proposed architecture has less slices than best existing designs. The proposed architecture is used in decimation filter of hearing aids applications using matlab simulink, which removes the unwanted signal.

A novel approach for optimal design of digital FIR filter using grasshopper optimization algorithm

The idea behind designing digital filters is to compute the optimal filter coefficients such that the magnitude response of the designed matches the ideal frequency response using optimization algorithms. The proposed work employed a recently proposed swarm-based optimization technique, namely, a grasshopper optimization algorithm (GOA) to design a linear phase finite impulse response (FIR) low pass, high pass, band pass , and band stop filters. This proposed algorithm models the behaviour of grasshoppers while seeking food sources to solve optimization problems. For the designing of the FIR filter, an absolute error difference fitness function is used, which is minimized using GOA to obtain optimal filter coefficients. The performance comparison of the proposed work is done with already existing algorithms such as cuckoo search, particle swarm optimization, artificial bee colony to prove its superiority and consistency. It is found that GOA based filter meets the objective efficiently with reduced ripples in pass band and higher attenuation in stop band with least execution time.