Butterworth filter

About: Butterworth filter is a research topic. Over the lifetime, 6187 publications have been published within this topic receiving 69070 citations.

Analysis of low-pass filters for approximate deconvolution closure modelling in one-dimensional decaying Burgers turbulence

Abstract: The idea of spatial filtering is central in approximate deconvolution large-eddy simulation AD-LES of turbulent flows. The need for low-pass filters naturally arises in the approximate deconvolution approach which is based solely on mathematical approximations by employing repeated filtering operators. Two families of low-pass spatial filters are studied in this paper: the Butterworth filters and the Pade filters. With a selection of various filtering parameters, variants of the AD-LES are systematically applied to the decaying Burgers turbulence problem, which is a standard prototype for more complex turbulent flows. Comparing with the direct numerical simulations, it is shown that all forms of the AD-LES approaches predict significantly better results than the under-resolved simulations at the same grid resolution. However, the results highly depend on the selection of the filtering procedure and the filter design. It is concluded that a complete attenuation for the smallest scales is crucial to prevent energy accumulation at the grid cut-off.

An Adaptive Outlier Detection and Processing Approach Towards Time Series Sensor Data

Abstract: The intelligent environment monitoring network, as the foundation of ecosystem research, has rapidly developed with the ever-growing Internet of Things (IoT). IoT-networked sensors deployed to monitor ecosystems generate copious sensor data characterized by nonstationarity and nonlinearity such that outlier detection remains a source of concern. Most outlier detection models involve hypothesis tests based on setting outlier threshold values. However, signal decomposition describes stationary and nonstationary relationships sensor data. Therefore, this paper proposes a three-level hybrid model based on the median filter (MF), empirical mode decomposition (EMD), classification and regression tree (CART), autoregression (AR) and exponential weighted moving average (EWMA) methods called MF-EMD-CART-AR-EWMA to detect outliers in sensor data. The first-level performance is compared to that of the Butterworth filter, FIR filter, moving average filter, wavelet filter and Wiener filter. The second-level prediction performance is compared to support vector regression (SVR), K-nearest neighbor (KNN), CART, complementary ensemble EEMD with CART and AR (EEMD-CART-AR) and ensemble CEEMD with CART and AR (CEEMD-CART-AR) methods. Finally, EWMA is compared to Cumulative Sum Control Chart (CUSUM) and Shewhart control charts. The proposed hybrid model was evaluated with a real dataset from the hydrometeorological observation network in the Heihe River Basin, yielding experimental results with better generalization ability and higher accuracy than the compared models, and providing extremely effective detection of minor outliers in predicted values. This paper provides valuable insight and a promising reference for outlier detection involving sensor data and presents a new perspective for detecting outliers.

Filter system with controlled amplitude in stopband or passband

Abstract: A filter system which may be configured either as a stopband (notch) or passband filter having controlled gain and low ripple throughout its stopband or passband. The system includes a filter network which is operative for splitting an input signal spectrum into a pair of complimentary spectrum components and a coupler for proportionately combining these spectrum components in accordance with a prescribed gain factor. The filter network may either comprise a pair of complimentary band reject and band pass filters connected to a common input terminal or a diplexer including identical filters coupled between a splitter and a combiner.

Half-Mode Substrate Integrated Waveguide (HMSIW) Filters and its Application to Tunable Filters

Abstract: —In this paper, novel bandpass filter and tunable bandpass filter are designed based on half-mode substrate integrated waveguide (HMSIW) embedded with complementary resonators Various passband characteristics are observed, and lumped equivalent circuit analysis models are developed The configuration of the proposed bandpass filter is an open structure, and it is easy to load the active devices and build the bias/control networks on the signal plane The tunable bandpass filter is presented based on the proposed novel bandpass filter loaded with semiconductor varactor diodes, and it has good spurious suppression characteristics and excellent out of band rejection The prototype with overall size of 159 mm × 302 mm × 05 mm was designed and fabricated so as to validate the new structure The measured central frequency is 1538 GHz and 1718 GHz, and the insertion loss is 51 dB and 33 dB, at 0 V and 30 V, respectively

Design of Artificial Transmission Line and Low-Pass Filter Based on Aperiodic Stubs on a Microstrip Line

Abstract: Among many microstrip configurations, the open-circuited shunt stub is probably the most common and versatile one. It is capable of performing a wide range of functions. Despite extensive studies and applications of the open-circuited shunt stub, comparatively little is known about aperiodic stubs on a microstrip line. In this paper, aperiodic stubs on a microstrip line are exploited to implement a high-performance low-pass filter and a joint design of the artificial transmission line and low-pass filter. The experimental results validate the performance of the proposed circuits. For the low-pass filter application, the proposed circuit outperforms a seventh-order Butterworth filter while their circuit sizes are comparable. For the joint design, it may potentially enhance the degree of integration in RF and microwave systems.