Lesion localization algorithm of high-frequency epileptic signal based on Teager energy operator

本文提出了基于希尔伯特–黄变换(Hilbert-Huang Transform, HHT)与Teager能量算子(Teager Energy Operator, TEO)相融合的谐振接地选线新方法。首先对零序电流信号进行经验模态分解法(Empirical Mode De-composition, EMD)分解，然后将TEO合理的引入选线算法中，并与HHT极性判别法相融合，实现了HHT与TEO两者融合的优势互补。通过仿真分析，验证了所提方法的可行性和有效性。 The combination method of Hilbert-Huang Transform (HHT) and Teager Energy Operator (TEO) for fault line selection with resonance grounding is proposed in this paper. The zero sequence current signals are decomposed using Empirical Mode Decomposition (EMD). The TEO is reasonable introduced into algorithm of fault line selection. The TEO is combined with the method of HHT polarity estimate. The complementary advantage for combination method of HHT and TEO is implemented. The feasibility and effectiveness of the proposed method is verified by simulation results.

The essence of finite impulse response (FIR) digital filter design is the problem of the parameter optimization. Namely the optimal parameters of FIR digital filter are the core of the design. In due to the traditional design method of FIR digital filter is not only accuracy not high but also sideband frequency is difficult to determine. Improve Weight Particle Swarm Optimization (IWPSO) to design FIR digital filter has less calculation and fast convergence speed. The simulation results also demonstrate that the IWPSO has better appro-ximation properties and band-pass characteristics. what’s more, the convergence of IWPSO algorithm made good results in filter design efficiency.

The traditional swarm intelligence optimization algorithm is prone to fall into local optimal solutions in finite impulse response (FIR) digital filter design and has slow convergence speed. In order to optimize the design of FIR filter, a FIR digital filter design method based on improved bee colony (ABC) algorithm is proposed. This improved ABC algorithm can adaptively adjust the step size of the selected neighborhood of nectar source location. At the same time, the information of the global optimal solution is used to guide the search of candidate solution, which improves the global search ability of the algorithm. The improved ABC algorithm can balance the conflict between local search ability and global search ability, so it can achieve better optimization effect. The time and space complexity of the algorithm is analyzed in detail. Then, the improved ABC algorithm is used to design three typical FIR digital filters, namely low-pass, band-pass and band-stop filter. The performance of the designed filter is tested by simulation experiments. The experimental results show that compared with other state-of-the-art optimization algorithms, the proposed FIR filter design method has achieved better effect and performance. Meanwhile, the proposed design method has shorter optimization time. The superiority of the proposed method is verified.

<span>The main purpose of this paper is to design a two-dimensional digital finite impulse response (FIR) filter using data broadcast and non-broadcast structure. The implementation of two-dimensional digital FIR filter is done using very high speed integrated circuit hardware description language (VHDL). Rectangular window method is used for calculating 2D digital FIR filter coefficients for data broadcast and non-broadcast structure. The coefficients of the one-dimensional digital FIR filter are obtained using the MATLAB filter design and analysis (FDA) tool for two different cut-off frequencies and are multiplied to get the necessary coefficient for the two-dimensional FIR filter to be designed; the simulation is done on Artix-7 series field programmable gate array (FPGA), target device (xc7a35t-cpg236) using Vivadov.2015.2. The proposed design reduces the area utilization and the power consumption when compared with the existing literature. The experimental result shows that the power consumption is improved by 97% and there is an improvement of 24% in area utilization for the two-dimensional with and without data broadcast one dimensional FIR filter structures.</span>

Area-time tradeoffs in FIR digital filters with broadcast and pipelined designs

Planetary gearboxes are widely used in the modern mechanical transmission equipment. The fault diagnosis of the planetary gearboxes is an important work. When the planetary gearbox fault occurs, its vibration signal has the characteristics of complex frequency components and amplitude modulation-frequency modulation. In view of these problems, a signal demodulation analysis method based on complementary ensemble empirical mode decomposition (CEEMD) and Teager energy operator is proposed to extract instantaneous amplitude and instantaneous frequency information of the fault signals. First, the CEEMD method is used to decompose the vibration signals of the complex multi component planetary gearbox into a series of single component intrinsic mode functions (IMFs). Then, the Teager energy operator is used to estimate the amplitude envelope and the instantaneous frequency of each single component signal. The intrinsic mode function is selected as the sensitive component according to the fluctuation characteristic of the instantaneous frequency. Finally, the Fourier transformation is applied in the obtained amplitude envelope and instantaneous frequency of the sensitive component to identify the gear fault characteristic frequencies, and achieve the accurate diagnosis of the planetary gearbox fault. The effectiveness and superiority of the method is verified through the analysis of the fault simulation experiment data of the planetary gearbox.

Epileptic seizure is the common neurological disorder, which is generally identified by electroencephalogram (EEG) signals. In this paper, a new feature extraction methodology based on optimum allocation sampling (OAS) and Teager energy operator (TEO) is proposed for detection of seizure EEG signals. The OAS scheme selects the finite length homogeneous sequence from non-homogeneous recorded EEG signal. The trend of selected sequence by OAS is still non-linear, which is analyzed by non-linear operator TEO. The TEO convert non-linear but homogenous EEG sequence into amplitude-frequency modulated (AM-FM) components. The statistical measures of AM-FM components used as input features to least squares support vector machine classifier for classification of seizure and seizure-free EEG signals. The proposed methodology is evaluated on a benchmark epileptic seizure EEG database. The experimental results demonstrate that the proposed scheme has capability to effectively distinguish seizure and seizure-free EEG signals.

This paper presents a new design method for parallel adaptive infinite impulse response (112) digital filters using Kalman filters in the time domain. the parallel Kalman filter (PKF) and the improved parallel Kalman filter (IPKF) based on the divided estimation of an unknown system's impulse response are extended to parallel adaptive IIR digital filters. the finite impulse response (FIR) digital filters can be replaced by reduced order IIR digital filters. This is particularly useful when high‐order FIR digital filters are necessary. A method is presented that ensures the stability of IIR digital filters with little extra computational effort.

This paper describes a new design algorithm for finite impulse response (FIR) digital filters, which approximates constant passband amplitude and linear phase characteristics. The algorithm converts a filter's specification characteristic into a continuous impulse response by using the frequency response of a window function. The continuous impulse response is translated into discrete values to calculate tap‐gain coefficients of an FIR filter. In this design algorithm, window functions belonging to the Hanning window series (such as the Harris' window whose characteristics are already known) are used. This design algorithm is an analytical design technique, featuring a filter length that can be decided when the specification is decided and does not require iterative numerical calculations to calculate tap‐gain coefficients.

Precise fault localization is vital for enhancing power grid reliability, reducing outage duration, and lowering maintenance expenses. This paper presents a fast and effective method that utilizes the application of voltage pulses with opposing polarities and identical durations to the transmission line. Analysis of traveling wave propagation under both normal and fault conditions indicates that the initial voltage wave observed in the non-injected phase stems from reflections at the fault point. The arrival time of the wavefront is accurately determined using variational mode decomposition (VMD) combined with the Teager energy operator (TEO) to pinpoint the fault location. Simulations conducted in PSCAD validate the efficacy of the proposed approach. This method demonstrates advantages including straightforward implementation, swift response, and superior accuracy compared to conventional techniques.

In this paper, a supervised learning method for the design of linear phase FIR digital filter using Keras is presented. First, the design problem of the linear phase finite impulse response (FIR) digital filter is transformed to a supervised learning problem. Then, the optimizers in Keras framework are used to determine the filter coefficients by minimizing the mean squared error (MSE) loss function. The widely-used optimizers include adaptive moments (Adam) algorithm and stochastic gradient descent (SGD) with momentum algorithm. Finally, the numerical design examples of low-pass and high-pass FIR digital filters are demonstrated to show the usefulness of the supervised learning method with Keras framework.

We investigate transmitter-side digital signal processing to generate 16-ary quadrature-amplitude-modulation (16QAM) Nyquist wavelength-division-multiplexing (WDM) signals by simulations. We first study required digital finite-impulse response (FIR) filter tap numbers and optimum roll-off factors to generate Nyquist 16QAM WDM signals. We show that a root-raised cosine spectrum with a roll-off factor of 0.1 is optimal for Nyquist 16QAM signals considering the tradeoff between the system performance and complexities, and a digital FIR filter with 37 taps is sufficient to generate such signals. Then we look into the effects of digital-to-analog converter (DAC) sampling speeds on the performance of Nyquist-WDM systems. We show that the electrical filter shape and spectral pre-emphasis have a big impact on the system performance. With a fourth-order super-Gaussian electrical filter and spectral pre-emphasis, DACs with 1.2 samples/symbol sampling speed can generate 16QAM Nyquist-WDM signals at 1.05-symbol-rate channel spacing, with an OSNR penalty below 0.2 dB compared with 2 samples/symbol DACs.

This paper presents architecture design techniques for implementing both single-rate and multirate high-speed finite impulse response (FIR) digital filters, with emphasis on the multirate multistage interpolated FIR (IFIR) digital filters. Well-known techniques to achieve high-speed and low-power applications for the single-rate digital FIR architecture are summarized, followed by the introduction of variable filter order selection, optimal filter decomposition, memory-saving and mirror symmetric filter pairs techniques which offer further gains in both performance and complexity reduction for the multirate multistage digital FIR architecture. A filter design example with TSMC 0.25 µm standard cell for 64-QAM baseband demodulator shows that the area is reduced by 39% for low-complexity application. Moreover, for high-speed application, the chip can operate at 714 MHz. Finally, a designed decimator which is used in the CDMA cellular shows that the area is reduced by 70% as compared with conventional approach.

Identification of fault in Thyristor Controlled Series Compensated (TCSC) compensated transmission system is challenging due to the nonlinear operation of the bidirectional thyristor, and Metal Oxide Varistor (MOV). Protection algorithms which use the current signature based on time or frequency domain analysis malfunction to propagate accurate information about fault condition. It can also happen that nonfaulty phases may detected as a faulty fault due to the replicated unbalance condition in the healthy phases. But such an issue can be resolved by extracting the fault generated components from three phases. In this way identification of accurate faulty phase will be easier. The frequency information in time domain revealed the presence of fault generated components. The same procedure is applied in this work to perform the fault identification task in TCSC line. The Empirical Mode Decomposition (EMD) incorporated with Teager Energy Operator (TEO) is used to extract and estimate the energy index of the most significant mode. Using the energy index fault identification process is accomplished in TCSC line. Results for different cases are provided which are obtained from the simulation of single and double circuit TCSC line. Both the lines are simulated using EMTDC/PSCAD software.

Chapter 2 - Design and Implementation of Digital FIR Filters