Orthogonal Wavelet Research Articles

Global Seismic Noise Entropy

Data of continuous records of low-frequency (periods from 2 to 1,000 min) seismic noise on a global network of 229 broadband stations located around the world for 23 years, 1997–2019, are analyzed. The daily values of the entropy of the distribution of the squares of the orthogonal wavelet coefficients are considered as an informative characteristic of noise. An auxiliary network of 50 reference points is introduced, the positions of which are determined from the clustering of station positions. For each reference point, a time series is calculated, consisting of 8,400 samples with a time step of 1 day, the values of which are determined as the medians of the entropy values at the five nearest stations that are operable during the given day. The introduction of a system of reference points makes it possible to estimate temporal and spatial changes in the correlation of noise entropy values around the world. Estimation in an annual sliding time window revealed a time interval from mid-2002 to mid-2003, when there was an abrupt change in the properties of global noise and an intensive increase in both average entropy correlations and spatial correlation scales began. This trend continues until the end of 2019, and it is interpreted as a feature of seismic noise which is connected with an increase in the intensity of the strongest earthquakes, which began with the Sumatran mega-earthquake of December 26, 2004 (M = 9.3). The values of the correlation function between the logarithm of the released seismic energy and the bursts of coherence between length of day and the entropy of seismic noise in the annual time window indicate the delay in the release of seismic energy relative to the coherence maxima. This lag is interpreted as a manifestation of the triggering effect of the irregular rotation of the Earth on the increase in global seismic hazard.

Comparison of Wavelet Packet and Wavelet in Solving Arbitrary Array of Parallel Wires Integral Equations in Electromagnetics

In this paper, wavelets transformation (WT) and wavelet packet transformation (WPT) are used in solving, by the method of moments, a semicircular array of parallel wires electric field integral equation. First, the integral equation is solved by applying the direct method of moments via point-matching procedure, results in a linear system with a dense matrix. Therefore, wavelet transformation and wavelet packet transformation are used to sparsify the impedance matrix, using two categories of wavelets functions, Biorthogonal (bior2.2) and Orthogonal (db4) wavelets. The far-field scattering patterns and the comparison between wavelets transformation and wavelet packet transformation in term number of zeros in impedance matrix and CPU Time reduction are presented. Numerical results are presented to identify which technique is best suited to solve such scattering electromagnetic problems and compared with published results.

Investigation of transient PVC dynamics in a strongly swirled spray flame using high speed planar laser imaging of SnO2 microparticles

Abstract The Precessing Vortex Core (PVC) dynamics is investigated in a laboratory scale swirl stabilized spray combustor. This helical structure commonly found in swirling flows used to stabilize flames in many combustion systems has a notable impact on the structure of the flow, spray and flame formed by the injector unit. The dynamics of the PVC is examined by combining laser sheet illumination of flame front tracers filmed with a high speed camera, Proper Orthogonal mode Decomposition (POD) and wavelet analysis. In distinction with most applications of laser sheet illumination, in which the flow is seeded with oil droplets that vanish at a relatively low temperature when crossing the flame front, the present implementation relies on micronic tin oxide (SnO 2 ) particles that vanish at much higher temperatures. This is well suited to flows where fresh reactants are already at high temperature or where hot gases are recirculated as is the case in most swirling injection configurations. A first set of experiments carried out with stagnation point premixed flames is used to determine the temperature ( T v ≈ 1770 K ) at which the tin dioxide particles vanish and to identify the chemical reaction that controls this process. Because the light scattered by the solid particles is quite intense, the method can be used at very high repetition rates. It is then applied at a 100 kHz frame rate to a swirling injection configuration in a situation where the flame is well stabilized and the combustor does not exhibit thermo-acoustic instabilities. It is found that the PVC takes the form of a double helix with brief intermittent switching to a single, followed by a triple helicoidal geometry. The POD-wavelet analysis indicates that these moments correspond to flashback events that randomly occur and during which the PVC characteristics change for a few milliseconds at a time. In a second set of experiments the chamber length is augmented giving rise to a combustion instability coupled by a longitudinal acoustic mode at a frequency that is an order of magnitude lower than the PVC frequency. The planar slices of the flame reveal a large cyclic motion of the lower edge of the flame in the inner recirculation zone. It is found that the PVC is modulated both in amplitude and frequency, the modulating frequency corresponding to that of the thermoacoustic oscillation. The double helix PVC is also observed to vanish in a random manner.

Influential Climate Teleconnections for Spatiotemporal Precipitation Variability in the Lancang‐Mekong River Basin From 1952 to 2015

AbstractThe Lancang‐Mekong River Basin (LMRB) in Mainland Southeast Asia is home to ~70 million people, mostly living in poverty and typically working in primary freshwater‐related sectors, particularly agriculture and fishery. Understanding the mechanisms of the historical variability in precipitation (as the crucial water source) plays a key role in regional sustainable development throughout the LMRB. Herein, the spatiotemporal variability in interannual and intra‐annual precipitation over the LMRB was analyzed using the Global Precipitation Climatology Centre (GPCC) data for the period 1952–2015. The empirical orthogonal function (EOF) and wavelet transform coherence methods were utilized to investigate the relationships of such historical variations in annual (water year: November–October), dry season (November–May), and wet season (June–October) precipitation with 13 different climate teleconnections (eight large‐scale oceanic‐atmospheric circulation patterns and five summer monsoons). On the basin scale, only a significant (p < 0.05) wetting trend in the dry season precipitation (DSP) was uncovered. Spatially, significant wetting (drying) trends in annual precipitation detected over the northeastern (most western) parts of the Mekong River Basin during the water years 1952–2015, largely contributed by the substantial increases (decreases) in historical wet season precipitation. The most important precipitation pattern (EOF1) was identified as a strong (relatively weak) positive center in the eastern (southwestern) Mekong River Basin accompanying by a significantly high (relatively low) positive value for the first EOF mode of the dry season precipitation (wet season precipitation). Precipitation variability in the LMRB was significantly associated with the South Asian Summer Monsoon Index, Southern Oscillation Index, and Indian Summer Monsoon Index.

Видалення шумових компонент інформаційних сигналів за допомогою ортогональних вейвлет-перетворень

Видалення шумових компонент інформаційних сигналів за допомогою ортогональних вейвлет-перетворень

Teleconnection patterns of precipitation in the Three-River Headwaters region, China

With the intensification of global warming, spatiotemporal variations in the climate and their mechanisms have received increasing attention. Currently, the relationship between regional precipitation regime, large-scale circulation, and topography, particularly in high-altitude areas such as the Qinghai–Tibet Plateau, are not well understood. Herein, the spatial and temporal variability in the annual and intra-annual (wet and dry periods) precipitation at 33 stations in the Three-River Headwaters (TRH) region from 1967 to 2016 are analysed. Moreover, the empirical orthogonal function and wavelet transform coherence methods are used to analyse the relationships between the different modes of precipitation change and 14 atmospheric circulation indices. The following results were obtained. (1) The mean annual precipitation and mean dry period precipitation significantly increased over the studied period. Annual and intra-annual precipitation showed a spatial southeast-to-northwest decreasing trend. (2) Two main patterns of precipitation were observed during the studied period: a dominant pattern with high- and low-value centres located in southeast and northwest TRH, respectively, and a dipole pattern with more precipitation over southwest TRH and less precipitation over northeast TRH. (3) Precipitation had a negative correlation with latitude, positive correlation with longitude, and nonlinear relationship with elevation. (4) Precipitation changes over various parts of the studied domain were determined based on changes in the weather systems affecting the area, with different indices being correlated with different components during different times of the year.

Three-dimensional multiscale flow structures behind a wall-mounted short cylinder based on tomographic particle image velocimetry and three-dimensional orthogonal wavelet transform.

Three-dimensional (3D) flow structures around a wall-mounted short cylinder of height-to-diameter ratio 1 were instantaneously measured by a high-resolution tomographic particle image velocimetry (Tomo-PIV) at Reynolds number of 10 720 in a water tunnel. 3D velocity fields, 3D vorticity, the Q criterion, the rear separation region, and the characteristic of arch type vortex and tip vortices were first discussed. We found a strong 3D W-type arch vortex behind the short cylinder, which was originated by the interaction between upwash and downwash flows. This W-type arch vortex was reshaped to the M-shaped arch vortex downstream. It indicated that the head shape of the arch vortex structure depended on the aspect ratio of the cylinder. The large-scale streamwise vortices were originated by the downwash and upwash flows near the center location of W-type arch vortex. Then the 3D orthogonal wavelet multiresolution technique was developed to analyze instantaneous 3D velocity fields of Tomo-PIV in order to clarify 3D multiscale wake flow structures. The W-type shape arch vortex was extracted in the time-averaged intermediate-scale structure, while an M-shaped arch vortex was identified in the time-averaged large-scale structure. The tip vortices distributed in the time-averaged large- and intermediate-scale structures. The instantaneous intermediate-scale upwash vortices played an essential role in producing W-type head of arch structure. It was also observed that strong small-scale vortices appeared in the shear layer or near the bottom plate and most of them were contained in the intermediate-scale structures.

Dominant pattern of year-to-year variability of summer precipitation in Nepal during 1987–2015

The study of inter-annual variability of summer precipitation is essential for Nepal as it manifests extreme events and thus impacts the socio-economy of the country. This study presents the dominant pattern of summer precipitation (JJAS) and its controlling phenomena during 1987–2015 over Nepal. Here, we used 0.25° × 0.25° APHRODITE and ERA5 reanalysis datasets to compute the empirical orthogonal function (EOF), wavelet, regression, and correlation analysis. The results show two dominant modes of EOF of summer precipitation over Nepal. EOF1 displays a single mode of variability with a 36.3% of variance, whereas EOF2 displays dipole mode of variability with 19.2% of variance, characterized by positive (negative) anomalies in the western (eastern) Nepal. The potential mechanism for the two leading modes is different. PC1 is highly negatively correlated with summer El Nino-Southern Oscillation (ENSO), whereas PC2 is the influence of the Indian Ocean Basin Mode (IOBM), which shows a strong significant negative relationship with the Indian Ocean from preceding spring to concurrent summer. Furthermore, PC1 is associated with strong easterly monsoonal wind flow from the Pacific Ocean and strengthening monsoonal trough over Nepal. However, in PC2, an anomalous low-level vertical circulation was observed between the Indian Ocean (divergence and anticyclonic circulation) and northern India (convergence and cyclonic circulation). The anomalous descending motion and cyclonic circulation strengthen the moisture transport to northern India, which plays a crucial role in increasing precipitation in western Nepal than eastern Nepal. This study provides useful information and underlying mechanism related to the summer monsoon variability of Nepal.

Seismic noise wavelet-based entropy in Southern California

Seismic noise properties in Southern California are considered. The initial data are continuous records of vertical oscillations with a sampling frequency of 1 Hz at 81 broadband stations for 12 years, 2008–2019. These data were converted to a time step of 1 min by calculating the average values in successive time intervals of 60 samples in length. The time series of low-frequency seismic noise with a time step of 1 min from each station was further converted to a sequence of daily values of the minimum normalized entropy of the distribution of the squared orthogonal wavelet coefficients. Since entropy estimates can be obtained from each station with a time step of 1 day, this makes it possible to construct a daily map of its changes in space. A general map of the distribution of entropy values is obtained by averaging daily maps. The main attention is paid to areas in which maximum entropy values are most often realized. These areas are identified by estimating the spatial probability density of the distribution of points at which a given number of maximum values are realized in each daily map. It has been shown that since 2012, the region of the most frequent realizations of entropy maxima is in direct contact with the epicenter of a strong earthquake on July 6, 2019, with magnitude 7.1. We consider the “secondary” entropy calculated for the probability densities of the distribution of the maximum values of the “primary” entropy of waveforms of seismic noise in a semi-annual moving time window. It is shown that the time intervals of increasing seismic activity correspond to a decrease in secondary entropy, which is interpreted as the concentration in the space of the distribution of the maxima of the primary noise entropy. Estimates of the change in the correlation coefficients between the daily values of the noise entropy in a semi-annual time window at network nodes of 12 reference points covering the region under study made it possible to study the spatiotemporal dynamics of strong correlations. The area of the future strong earthquake is characterized by high correlations of entropy values at the nearest reference points with other points.

A Numerical Method for Boundary Value Problems for a Homogeneous Equation with the Squared Laplace Operator with the Use of Interpolating Wavelets

We present an effective numerical method for the recovery of biharmonic functions in a disk from continuous boundary values of these functions and of their normal derivatives using wavelets that are harmonic in the disk and interpolating on its boundary on dyadic rational grids. The expansions of solutions of boundary value problems into cumbersome interpolation series in the wavelet basis are replaced by sequences of their partial sums that are compactly presentable in the subspace bases of the corresponding multiresolution analysis (MRA) of Hardy spaces $$h_{\infty}(K)$$ of functions harmonic in the disk. Effective estimates are obtained for the approximation of solutions by partial sums of any order in terms of the best approximation of the boundary functions by trigonometric polynomials of a slightly smaller order. As a result, to provide the required accuracy of the representation of the unknown biharmonic functions, one can choose in advance the scaling parameter of the corresponding MRA subspace such that the interpolation projection to this space defines a simple analytic representation of the corresponding partial sums of interpolation series in terms of appropriate compressions and shifts of the scaling functions, skipping complicated iterative procedures for the numerical construction of the coefficients of expansion of the boundary functions into series in interpolating wavelets. We write solutions using interpolating and interpolating-orthogonal wavelets based on modified Meyer wavelets; the latter are convenient to apply if the boundary values of the boundary value problem are given approximately, for example, are found experimentally. In this case, one can employ the usual, well-known procedures of discrete orthogonal wavelet transformations for the analysis and refinement (correction) of the boundary values.

Damage detection in connections of steel moment resisting frames using proper orthogonal decomposition and wavelet transform

Dynamic characteristics of the structures such as natural frequencies, mode shapes and damping, are inherent parameters of structures which change as a result of local damages. Damage detection using mode shape curvature difference method is too sensitive to the presence of noise. This paper introduces a new method for damage detection in the connection of steel moment resisting frames. This method is based on the mode shape curvature. The damages are localized using first proper orthogonal decomposition (POD) mode shape combination with wavelet transform, accurately. A new method has been used for calculating the curvature at the beginning and end of the members. This procedure has been studied on one span three story experimental moment frame and also on various steel frame numerical model, in different damage scenarios. The results of this research show that the proposed method can detect damage in moment connections with an acceptable accuracy.

Transformasi Wavelet dengan Teknik Clipping Filtering untuk Mereduksi PAPR pada OFDM

Orthogonal Frequency Division Multiplexing (OFDM) is chosen as multiplexing techniques and broadly used in today’s radiocommunication environments to overcome spectrum insufficiency. With several superior advantages, however, OFDM is terribly affected by high peak to average power ratio (PAPR) due to offset frequency errors and local oscillator (LO) frequency synchronization errors. The high PAPR can cause nonlinear distortion, which outcomes in intermodulation and spectral leakage. This study aims to model the use of wavelet transform (discrete wavelet transform (DWT)) to replace Fourier transform (discrete Fourier transform (DFT)) that used in conventional OFDM, later in this paper is termed as DFT-OFDM. Clipping filtering techniques then applied to DWT-OFDM. The model was proposed to reduce PAPR in DFT-OFDM. The model was compared to DFT-OFDM using Matlab simulation method. The performance was evaluated using the Complementary Cumulative Distributive Function (CCDF) vs. PAPR. The results show that at PAPR 10-3for DFT-OFDM, it was produced PAPR of 10.6 dB whereas in DWT-OFDM, using Daubechies orde 7 (Daubechies7), Symlet orde 7 (Symlet7), Coiflet orde 2 (Coiflet2), were reached PAPR 4.8 dB, PAPR 3.3 dB, PAPR 3 dB, respectively. It means Coiflet2 providing the best PAPR reduction among other orthogonal wavelets. By applied clipping filtering to wavelet Coiflet2, it was produced PAPR of 2.9 dB for classical clipping and 2.8 dB for deep clipping. It show that wavelet Coiflet2 with deep clipping provided the best PAPR.

Correspondence between multiwavelet shrinkage and nonlinear diffusion

Wavelet/frame shrinkage and nonlinear diffusion filtering are two popular methods for signal and image denoising. The relationship between these two methods has been studied recently. This relationship leads to new types of diffusion equations and helps to design the wavelet/frame-inspired diffusivity functions, and on the other hand it helps to design the diffusion-inspired shrinkage functions with a better performance in signal and image denoising.Multiwavelets have important properties such as orthogonality, short support, and symmetry, etc. that scalar orthogonal wavelets cannot possess simultaneously. There is rich literature on the theoretical study, construction and applications of multiwavelets. In particular, it has been shown that multiwavelets perform better than the scalar wavelets in signal and image denoising. Recently multiwavelet denoising has been applied in different applications including rolling bearing fault detection and study of load spectrum of computer numerical control lathe. Therefore it is worth to further study multiwavelet denoising.In this paper we investigate the correspondence between multiwavelet denoising and nonlinear diffusion. We show that the multiwavelet shrinkages of the commonly used CL(2) and DGHM multiwavelets are associated with a second-order nonlinear diffusion equation. We also derive high-order nonlinear diffusion equations associated with general multiwavelet shrinkages. The experimental results carried out in this paper show that the diffusion-inspired multiwavelet shrinkage performs better than the traditional multiwavelet hard- and soft-thresholding shrinkages.

On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications.

This paper presents a compression study of electrocardiogram (ECG) signals for e-Health cardiac online diagnostic systems. The study uses 75 real electrocardiogram records sampled with continuous-time level-crossing (LC) analog-to-digital converter (ADC). This signal-dependent LC-ADC compresses signals compared to conventional ADC but further compression is needed especially for long-time monitoring applications. The orthogonal matching pursuit algorithm is simulated to evaluate ECG compression with 54 orthogonal and biorthogonal wavelets. For LC-ADC amplitude output compression, Biorthogonal3.1 (bior3.1) wavelet achieves optimal performances in terms of compression ratio (CR) while ensuring 2-% percentage root-mean-square difference (PRD). The PRD must be limited to this value to ensure a very good quality signals after decompression. For circuit implementation purposes, bior3.1 wavelet is proposed as a multiplier-free decomposition step and a noncomplex global and hard thresholding process is achieved. The average CR is 63% and PRD varies between 0.1 and 2.1% leading to a very good diagnostic quality.

Assessing spatiotemporal characteristics of drought and its effects on climate-induced yield of maize in Northeast China

It is important to investigate the potential impacts of global climate change on crop yield especially there have been limited relevant studies conducted in the cold regions such as Northeast China. This study investigated the spatiotemporal characteristics of droughts on different growth stages of maize over Northeast China during 1960–2016 and the effects of droughts on the climate-induced yield of maize separated by the logistic regression model using standardized precipitation evapotranspiration index (SPEI), trend analysis methods, rotated empirical orthogonal function, wavelet method, and Hurst exponent. The results indicated that: 1) the spatiotemporal patterns of drought were identified at different growth stages and the changes in dryness/wetness condition presented significant periodic oscillation on different time scales. 2) The patterns of dryness/wetness conditions and the changing characteristics of each sub-region at the early growth (EG) and middle growth (MG) stages were similar. 3) The future drought trends in most stations would be consistent with the past trends. In addition to the wetting trend in the eastern and southern parts at the EG stage, the whole study area would show a drying trend in future at other growth stages. 4) The cross wavelet transform (XWT) was used to develop the changing relationships between climate-induced yield of maize and the dryness/wetness condition at different growth stages with obvious inter-annual periodicities. 5) For Northeast China, climatic factors that can affect the climate-induced yield of maize are firstly temperature, next precipitation, and thirdly dryness/wetness conditions.

Inter-Annual Variability of Winter Precipitation Over Nepal Coupled With Ocean-Atmospheric Patterns During 1987–2015

Nepal is a mountainous country located on the southern slope of the central Himalayas, where ~3% of the total annual rainfall occurs in the winter season. The inter-annual variability and shift in the winter precipitation are of great importance in space and time, however, has not been investigated in Nepal. This study sought to investigate the inter-annual variability of winter precipitation (DJF), below- and above-average winter precipitation anomalies over Nepal and their controlling factors associated with ocean-atmospheric circulation patterns during the historical period of 1987–2015. Here, we used Asian Precipitation-Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE), Climate Prediction Center (CPC) database of National Centres for Environmental Prediction (NCEP) and Japan Marine Science and Technology Centre (JAMSTEC) data from different sources to study the Empirical Orthogonal Function (EOF), Wavelet, Composite, and Correlation analysis, respectively. The results show that the leading EOF mode captures 62.1% of the total variance of precipitation exhibiting a single mode of variability. As determined by wavelet analysis, the winter precipitation of Nepal shows 2 to 2.6 year’s power spectrum for 29 years (1987–2015). The time series of winter precipitation anomalies revealed the years 1996, 1998, 2000, 2005, 2007, and 2008 as precipitation deficit years which is supported by the composite analysis showing negative precipitation anomalies with positive outgoing longwave radiation (OLR) and vertical velocity. These phenomena are converse for wet events during 1988, 1995, 1997, 2002, 2012, and 2014. The wet years exhibit moisture convergence with strong south-westerly wind anomalies originated from the Arabian Sea. The dry events reveal moisture divergence with weaker north-westerly wind anomalies. The temperature gradient over Tibetan Plateau is linked with a shift in precipitation regime over Nepal. The further finding indicates that preceding summer monsoon (JJAS) and post-monsoon (ON) warming over the Indo-Pacific Ocean influences the following year's winter precipitation over Nepal. The observed changes in the dry and wet years during winter are useful for disaster preparedness and the planning and monitoring of water resources and agriculture.

Multi-time scale based modeling of piezoelectric materials coupling transient electrical and dynamic fields with finite deformation damage

This paper develops a high performance scalable computational model for simulating coupled transient electric and finite deformation dynamic fields with widely discrepant frequencies, governing the behavior of piezoelectric materials in the finite element framework. The nonlinear piezoelectric constitutive laws are formulated in the context of continuum damage models (CDM) at finite deformation. A fully coupled, total Lagrangian finite element formulation is developed for modeling the electric and mechanical fields in a staggered way. To address the computational challenge in modeling piezoelectric devices with large discrepancy in the frequenlightsghtscies of the electrical signal and mechanical vibrations, a wavelet transformation induced multi-time scaling (WATMUS) algorithm is developed. The WATMUS method projects the field with higher frequency onto the lower frequency problem through the use of orthogonal wavelet transformation. No assumption of periodic response is needed in the WATMUS scheme. While being accurate, the WATMUS algorithm significantly enhances the computational efficiency in comparison with single time scale integration methods. The accuracy and efficiency of the WATMUS algorithm are validated through piezoelectric applications.

Signal Reconstruction Using New Biorthogonal Frequency-Modified Kravchenko Wavelets When Representing the Measurement Process as a Convolution Model

Abstract—A new biorthogonal system of wavelet bases has been constructed, which is oriented toward reconstructing the useful signal of a measuring system if the measurement process is represented as a convolution model. New biorthogonal wavelet bases are obtained by using a instrumental function to modify a Kravchenko orthogonal wavelet system with a finite spectrum. The properties of new biorthogonal frequency-modified wavelets are studied, and digital filters that realize fast computational algorithms are constructed. Schemes for multiresolution analysis are proposed, which, during discrete wavelet transform, immediately solve the problem of reconstructing the useful signal, as well as effective noise suppression, which can significantly speed up computations.

Harmonic Interpolating Wavelets in a Ring

Complementing the authors' earlier joint papers on the application of orthogonal wavelets to represent solutions of Dirichlet problems with the Laplace operator and its powers in a disk and a ring and of interpolating wavelets for the same problem in a disk, we develop a technique of applying periodic interpolating wavelets in a ring for the Dirichlet boundary value problem. The emphasis is not on the exact representation of the solution in the form of (double) series in a wavelet system but on the approximation of solutions with any given accuracy by finite linear combinations of dyadic rational translations of special harmonic polynomials; these combinations are constructed with the use of interpolating wavelets. The obtained approximation formulas are simply calculated, especially if the squared Fourier transform of the Meyer scaling function with the properties described in the paper is explicitly defined in terms of the corresponding elementary functions.

Automated detection of abnormal EEG signals using localized wavelet filter banks

Epilepsy is a neural disorder that is associated with the central nervous system (CNS) in which the brain activity sometimes becomes abnormal, which may lead to seizures, loss of awareness, unusual sensations, and behavior. Electroencephalograms (EEG) are widely used to detect epilepsy accurately. However, the interpretation of a particular type of abnormality using the EEG signal is a subjective affair and may vary from clinician-to-clinician. Visual inspection of the EEG signal by observing a change in frequency or amplitude in long-duration signals is an arduous task for the clinicians. It may lead to an erroneous classification of EEGs. The proposed methodology focuses on automated detection of epilepsy using a novel stop-band energy (SBE) minimized orthogonal wavelet filter bank. Using the wavelet decomposition, we obtain subbands (SBs) of EEG signals. Subsequently, fuzzy entropy, logarithmic of the squared norm, and fractal dimension are computed for each SB. The different combinations of the extracted features were supplied to various classifiers for the classification of normal and abnormal EEG signals. In the proposed method, we have used a single-channel EEG dataset of Temple University Hospital. The dataset is the most substantial EEG data publicly available, which contains an EEG recording of 2130 distinct subjects. Our proposed system obtained the highest classification accuracy (CACC) of 78.4% and 79.34% during training and evaluation using the SVM classifier. We achieved the highest F1-score of 0.88.