•Estimating recession constant is key to the one-parameter digital filtering.•The Eckhardt method is sensitive to the maximum baseflow index.•Difference among the improved digital filtering methods ...is small.•The improved Lyne–Hollick method with two passes performs overall best.
Baseflow is the portion of streamflow that comes from shallow and deep subsurface flow, and is the key for catchment ecology and water resource management. This paper comprehensively evaluates four widely used non-tracer baseflow separation methods against tracer-based hydrograph separation for five Eastern Australian catchments. The four methods include United Kingdom Institute of Hydrology (UKIH) method and three digital filtering methods: Lyne–Hollick method, Chapman–Maxwell method and Eckhardt method. The first two filtering methods include a parameter of recession constant, and the last one has two parameters: the recession constant and the maximum baseflow index. We used an Automatic Baseflow Identification Technique (ABIT) to estimate the recession constant, which varies from 0.943 to 0.987 for the five catchments that is evidently higher than the default value of 0.925, and used the default Eckhardt and UKIH methods to estimate the maximum baseflow index, respectively. All modelling results are evaluated against the tracer-based hydrograph separation. Using the recession constant estimated from the ABIT method performs noticeably better than using the default parameter, indicated by the absolute bias reduced about 20% in average. For the two-parameter Eckhardt method, estimating the maximum baseflow index has larger effect on baseflow separation than estimating the recession constant. Compared to the different parameterisation schemes, the difference among the improved non-tracer methods is small. Using multiple passes into the Lyne–Hollick method can only slightly improve or deteriorate baseflow index estimates. Our results suggest that it is critical to get appropriate parameter(s) before applying the digital filtering methods.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
We investigate the generation of free-stream perturbations at a relatively low characteristic Reynolds number of 1000 by means of direct numerical simulations using a synthetic turbulence generation ...method. This approach consists of generating turbulent fluctuations by means of digital filtering and a source term formulation in the Navier–Stokes equations. To assess its validity in the framework of decaying turbulence, we compare the results with those obtained with a physically-based, grid-induced turbulent flow in terms of spatial decay, evolution of characteristic length-scales and energy spectra. Also, we highlight relevant differences such as those in the streamwise development length and the anisotropy of the largest scales. Then, we characterize the generated perturbations when systematically varying the input parameters, namely the initial integral length-scale and turbulence intensity. Here, we notice differences in the streamwise decay of the turbulence intensity and the development length as we vary these parameters. By inspecting the evolution of the characteristic length-scales and the micro-scale Reynolds number, we also identify that the effective scale separation is highly sensitive to these variations.
•Free-stream turbulence generated via a digital-filter synthetic approach and DNS.•Direct comparison with experimental-like, grid-induced turbulence approach.•Study over the influence of input parameters on characteristic flow features.•Characterization in terms of decay’s large-scale observables and energy spectra.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The fast increase of the amount of quantitative and qualitative characteristics of digital visual data calls for the improvement of the performance of modern image processing devices. This article ...proposes new algorithms for 2D digital image processing based on the Winograd method in a general form. An analysis of the obtained results showed that the use of the Winograd method reduces the computational complexity of image processing by up to 84% compared to the traditional direct digital filtering method depending on the filter parameters and image fragments, while not affecting the quality of image processing. The resulting Winograd method transformation matrices and the algorithms developed can be used in image processing systems to improve the performance of the modern microelectronic devices that carry out image denoising, compression, and pattern recognition. Research directions that show promise for further research include hardware implementation on a field-programmable gate array and application-specific integrated circuit, development of algorithms for digital image processing based on the Winograd method in a general form for a 1D wavelet filter bank and for stride convolution used in convolutional neural networks.
The emergence of advanced technologies has spurred the development of high-capacity, long-distance, and high-speed coherent optical communication systems. However, Chromatic Dispersion (CD) is the ...major challenge of coherent optical communication leading to high power consumption at the receiver which impedes the adoption of the technology. The existing systems adopt a high-complexity FFT-based CD equalization consuming around 20% power in the receiver. In this paper, we propose DFNT-TrDE, an efficient Transform Domain Equalization (TrDE) method that reduces the computational complexity of the CD compensation by leveraging the Fermat Number Transform (FNT, where Fermat number <inline-formula><tex-math notation="LaTeX">F_{n} = 2^{b}+1=2^{2^{n}}+1</tex-math></inline-formula>) with diminished-1 representation. We adopt various techniques in the system design. Specifically, we propose High-Radix (HR) FNT to further reduce the complexity for large transform lengths. Moreover, we compare the complexity of 1D circular convolution between 1D-R2, 1D-HR, 2D-R2 and 2D-HR FNT at the granularity of adder level. We furthermore provide recommendations for radix and dimension settings tailored to different transform lengths. The results of our implementation show that the DFNT-TrDE (with <inline-formula><tex-math notation="LaTeX">b=8</tex-math></inline-formula>) achieves 62% complexity savings compared to 12-bit split-radix FFT-FDE at a similar Bit Error Rate (BER). The DFNT-TrDE (with <inline-formula><tex-math notation="LaTeX">b=16</tex-math></inline-formula>) also achieves 51% complexity savings compared to 16-bit split-radix FFT-FDE at a better BER.
Previous studies showed that 4DVar (Four-dimensional Variational) technique used for data assimilation could be modified for weather control and ours demonstrated the ability of 4DVar to influence ...the moving track of a typhoon by calculating perturbations in WRF simulation. To improve the effect of weather control, the model error resulting from the high-frequency oscillation noise in 4DVar is considered in this paper. Numerical experiments have been conducted on typhoon Mitag and typhoon Malakas respectively. In one experiment, after the 4DVar weather control tests considering the digital filtering, the wind field in the initial field changes obviously. In another, the analysis increment for wind field after digital filtering changes noticeably, while the effect on temperature field is relatively small. The results show that the setting of digital filtering has an obvious influence on the wind field at the initial state, signifying that digital filtering as weak constraints of 4DVar can filter out the influence of high-frequency oscillation noise to some extent. The digital filtering plays a considerable role on the prediction of typhoon track and intensity, capable of further reducing the forecast error of typhoon. Moreover, the prediction results are less sensitive to the weight of the digital filtering.
•4DVar(Four-dimensional Variational) technique used for data assimilation could be altered for weather modification.•The weak constraint of digital filtering can filter out the influence of high-frequency oscillation noise to some extent.•Considering digital filtering as weak constraints in the weather control version of 4DVar yields a more precise disturbance field.The prediction results are less sensitive to the weight of the digital filtering.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
With the improvement of medical level, electrocardiogram (ECG) is widely used for disease diagnosis. A lot of pathological and physiological information is contained in the ECG, which can be ...used to record the point activity of normal human heart and diagnose various heart disease. However, the acquired ECG signals are always contaminated with noise which caused by acquisition equipment or other circumstance. Therefore, Efficient denoising method is very important. In this paper, three typical ECG signal denoising methods are listed, including FIR filtering, wavelet filtering and EMD filtering. In this paper, the principles of the three filtering methods are introduced in detail, and their effects are compared. By comparison, it intuitively shows the processing effects of each method on ECG signals. Meanwhile, a simple Butterworth filter is designed to denoise a standard wave, which represents the logic knowledge related to denoising. It is very significant for the medical signal processing field and help to research more effective signal processing methods.
The issues related to the problem of minimizing hardware costs in the digital algorithms’ hardware and software implementation for the discrete signals’ frequency selection on programmable logic ...devices (PLD) and special processor microelectronic devices are considered. Possible ways to solve these problems are described based on the computational algorithms for non-recursive digital filtering (NDF) and difference digital filtering with integer coefficients use. A necessary and sufficient condition is given for using a computational algorithm’s hardware and software implementation of discrete signals’ difference digital filtering for their multi-stage discrete Fourier transform without performing arithmetic multiplication operations.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Epilepsy seizure prediction has become one of the interesting fields that attract researchers to innovate solutions. For epilepsy patients, Electroencephalography (EEG) signals consist of three ...activities: normal, pre-ictal and ictal. In order to design a prediction model for the ictal state, it is required to distinguish between the activities of EEG signals. This paper presents efficient seizure prediction approaches from EEG signals based on statistical analysis, digital band-limiting filters and artificial intelligence. Band-limiting filters are used to remove out-of-band noise and spurious effects. Then, statistical analysis is adopted for channel selection and seizure prediction based on a thresholding strategy. This statistical analysis depends on amplitude, median, mean, variance and derivative of the EEG signal. The adopted band-limiting filter affects the seizure prediction metrics such as accuracy, prediction time and false alarm rate. The prediction process consists of two phases: training and testing. Both k-means clustering and Multi-Layer Perceptron (MLP) networks are considered for seizure prediction based on artificial intelligence. The proposed approaches can be implemented in a mobile application to give alerts to patients or care givers. The simulation results reveal that the proposed approaches present high performance in terms of accuracy, prediction time and false alarm rate.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Fundamental phasor estimation is one of the most important jobs to be done by the digital protective relay (DPR). However, fault signals given to DPR consist of decaying DC (DDC) components, ...harmonics, and noise which can lead to inaccuracy in phasor estimation. Hence, for accurate results, digital filtering algorithms (DFAs) are mandatory to wipe out all these unwanted components. In modern DPR, discrete Fourier transform (DFT) is extensively used DFA for fundamental phasor estimation. However, the accuracy of DFT is affected by the presence of DDC. Hence, to tackle this problem, a new real-time fast DFA based on the mathematical morphology (MM) technique is put forward. First, the DDC components are filtered out using the morphological median filter (MMF) and are subtracted from the original fault signal. Afterwards, the fundamental phasor is extracted from the residual DDC-free signal using the DFT. Several computer-simulated, EMTP-generated, and real-field fault signals are used to examine the efficacy of the proposed DFA. In addition, the proposed DFA is compared with other existing techniques. The obtained results prove that the suggested DFA has vigorous performance in the presence of multiple DDC components, noise, and severe harmonic conditions with a low computational burden and high accuracy.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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