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Robust Spike Sorting Using dual tree complex wavelet transform: Overcoming Traditional Limitations

IEEE ACCESS 2025年 13卷 3497-3511页

作者： Serbes, Gorkem Yildiz Tech Univ Fac Elect & Elect Engn Dept Biomed Engn TR-34220 Istanbul Turkiye

Accurate spike sorting is vital for understanding the neural network dynamics of the brain through extracellular neural recordings. Traditional feature extraction methods like the Haar wavelet and principal component analysis (PCA) face limitations in high-noise environments and when dealing with similar spike waveforms. This study proposes the use of the dual-tree complex wavelet transform (DT-CWT), which is an enhanced version of the traditional discrete wavelet transform, as a feature extractor in spike sorting. The proposed approach aims to leverage the approximate shift invariance and superior time-frequency localization capabilities of the DT-CWT in spike discrimination. A simulated dataset with varying noise levels and spike waveform similarities was used for validation. The performance of DT-CWT was compared with Haar wavelet and PCA using both original and modified superparamagnetic clustering approaches. Results demonstrated that the DT-CWT-based feature extraction achieved significantly lower average error rates across all subsets, especially in challenging conditions with high noise and similar waveforms. Moreover, the DT-CWT's computational efficiency and suitability for real-time, on-chip implementations in next-generation wireless brain computer interface devices highlight its practical advantages. By providing robust and discriminative features under stringent resource constraints, the DT-CWT-based approach outperforms traditional methods, establishing itself as a preferred choice for scalable and efficient spike sorting in demanding scenarios.

关键词： Spike sorting dual tree complex wavelet transform feature extraction superparamagnetic clustering time-frequency analysis approximate shift invariance noise robustness Spike sorting dual tree complex wavelet transform feature extraction superparamagnetic clustering time-frequency analysis approximate shift invariance noise robustness

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dual tree complex wavelet transform approach to copy-rotate-move forgery detection

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Science China(Information Sciences) 2014年第1期57卷 125-136页

作者： WU YunJie DENG Yu DUAN HaiBin ZHOU LinNa Science and Technology on Aircraft Control Laboratory BeiHang University Department of Electronics Engineering Tsinghua University

As a common scheme of image tampering,copy-move forgery plays an important role in image forgery *** several blind methods aimed at detecting replicated regions have been proposed,these methods cannot detect the rotation changes in the duplicated areas *** this paper,a new forensic method is presented to detect the replicated areas rotated by arbitrary angles,even by JPEG *** achieve this,overlapping blocks of pixels are decomposed using dual tree complex wavelet transform(DTCWT),and then channel energies are extracted from each subband at each decomposition level using the ***,the anisotropic rotationally invariant features are extracted using magnitudes of discrete Fourier transform for these channel *** implementation procedure of the proposed method is described in *** experimental results,including a comparative evaluation with existing methods and the special applications in practice,are also presented to demonstrate the robustness and efectiveness of the proposed method.

关键词： digital image forgery digital image forensic copy-rotate-move forgery dual tree complex wavelet transform

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dual tree complex wavelet transform based analysis of epileptiform discharges

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International Journal of Information Technology (Singapore) 2018年第4期10卷 543-550页

作者： Khan, Ayesha Tooba Khan, Yusuf Uzzaman Department of Electrical Engineering Aligarh Muslim University Aligarh India

Diagnosis of epileptic seizures entails visual inspection of complex seizure patterns which is a tedious task. Development of automated systems for analysing brain activity would significantly minimise the epilepsy treatment gap by providing assistance to neurophysiologists. Present research work is intended to provide insight to the epileptiform discharges during the seizures using dual tree complex wavelet transform. Algorithm is developed using publically available data from Bonn University. Statistical and nonlinear features, selected on the basis of Bhattacharyya distance, are extracted from EEG segments to demarcate the seizure and nonseizure EEG boundaries. Quadratic classification of EEG features followed by k-fold cross validation with varying train to test ratios is employed to develop a generalised robust model. Performance of classifier is accessed in terms of statistical parameters. © 2018, Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Classification dual tree complex wavelet transform EEG K-fold cross validation Seizure detection

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dual tree complex wavelet transform Based Approach for Power Quality Monitoring and Data Compression 2

Dual Tree Complex Wavelet Transform Based Approach for Power...

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2nd Biennial International Conference on Power and Energy Systems - Towards Sustainable Energy (PESTSE)

作者： Prathibha, E. Manjunatha, A. Basavaraj, Sunil Sri Krishna Inst Technol Elect & Elect Engn Dept Bangalore Karnataka India

ISBN: (纸本)9781467366588

Power quality disturbance is a one the challenging issues, where many researchers are gaining the attention towards it, now a day it is very much necessary to monitor power quality disturbances for analyze and other purpose. The quantity of the data captured in present power quality monitoring system has been increasing drastically. It is difficult to store and transmission huge data. So compression technique is required to reduce the storage space for data. This paper proposes dual tree complex wavelet transform (DTCWT) method for power quality monitoring and integrates run length encoding technique for compress disturbance data. Voltage sag, swell, transients and flickers are Power quality disturbances used to test the proposed method. And Matlab was used for generation of test signals and to implement the different algorithms for data compression.

关键词： Power Quality Disturbances dual tree complex wavelet transform Feature extraction Data compression

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dual tree complex wavelet transform Based Speech Enhancement 23

Dual Tree Complex Wavelet Transform Based Speech Enhancement

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23nd Signal Processing and Communications Applications Conference (SIU)

作者： Tasmaz, Haci Adiyaman Univ Muhendisl Fak Elekt Elekt Muhendisligi Bolumu Adiyaman Turkey

ISBN: (纸本)9781467373869

dual tree complex wavelet transform (DT-CWT) has the advantages of nearly shift-invariance and directional selectivity (for two or more dimensions) over the classical discrete wavelet transform. These advantages are essential for many signal processing applications (i.e. image fusion, image enhancement, pattern recognition). In his study, a speech enhancement method based on the DT-CWT has been proposed in order to test its performance in speech enhancement. An efficient estimator, multiplicatively modified log-spectral amplitude (MM-LSA) estimator is used for the enhancement of noisy subband wavelet coefficients. The objective and experimental results show the superiority of the proposed method to the wavelet transform based methods well known in the literature.

关键词： speech enhancement discrete wavelet transform wavelet packet transform lifting wavelet transform stationary wavelet transform dual tree complex wavelet transform multiplicatively modified log-spectral amplitude estimator

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dual tree complex wavelet transform Based Sperm Abnormality Classification 41

Dual Tree Complex Wavelet Transform Based Sperm Abnormality ...

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41st International Conference on Telecommunications and Signal Processing (TSP)

作者： Ilhan, Hamza Osman Serbes, Gorkem Aydin, Nizamettin Yildiz Tech Univ Dept Comp Engn Istanbul Turkey

ISBN: (纸本)9781538646953

In the proposed study, dual tree complex wavelet transform (DTCWT) based statistical features that are derived from normal sperm, abnormal sperm and non-sperm patches are fed to Support Vector Machine classifier with the aim of three class discrimination. The obtained results are compared with the classical dyadic discrete wavelet transform and the superiority of the proposed method has been shown in terms of accuracy and F-measure metrics. The results show that higher accuracy and F-measure scores have been obtained with the proposed approach due to the shift invariance and better direction selectivity property of the DTCWT.

关键词： Discrete wavelet transform dual tree complex wavelet transform Support Vector Machines Sperm Abnormality Classification

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dual tree complex wavelet transform based Multiclass Object Classification

Dual tree complex wavelet transform based Multiclass Object ...

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12th International Conference on Machine Learning and Applications (ICMLA)

作者： Khare, Ashish Khare, Manish Srivastava, Rajneesh Kumar Univ Allahabad Dept Elect & Commun Image Proc & Comp Vis Lab Allahabad 211002 Uttar Pradesh India

ISBN: (纸本)9780769551449

Multiclass object classification is a difficult problem in computer vision application, because of highly variable nature of different objects. The primary goal of this paper is to classify object into one of the chosen classes. The proposed method uses dual tree complex wavelet transform coefficients as a feature of object. dual tree complex wavelet transform is having advantage of its better edge representation and approximate shift-invariant property as compared to real valued wavelet transform. We have used multiclass support vector machine classifier for classification of objects. The proposed method has been tested on dataset prepared by authors of this paper. We have tested the proposed method on multiple levels of dual tree complex wavelet transform. Quantitative evaluation results demonstrate that the proposed method gives better performance for multiclass object classification in comparison to other state-of-the-art methods.

关键词： dual tree complex wavelet transform Multiclass object classification Feature selection

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dual tree complex wavelet transform based Shadow Detection and Removal from Moving Objects

Dual Tree Complex Wavelet Transform based Shadow Detection a...

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Conference on Visual Information Processing and Communication V

作者： Khare, Manish Srivastava, Rajneesh Kumar Khare, Ashish Univ Allahabad Dept Elect & Commun Allahabad 211002 Uttar Pradesh India

ISBN: (纸本)9780819499462

Presence of shadow degrades performance of any computer vision system as a number of shadow points are always misclassified as object points. Various algorithms for shadow detection and removal exist for still images but very few algorithms have been developed for moving objects. This paper introduces a new method for shadow detection and removal from moving object which is based on dual tree complex wavelet transform. We have chosen dual tree complex wavelet transform as it is shift invariant and have a better edge detection property as compared to real valued wavelet transform. In the present work, shadow detection and removal has been done by thresholding wavelet coefficients of dual tree complex wavelet transform of difference of reference frame and the current frame. Standard deviation of wavelet coefficients is used as an optimal threshold. Results after visual and quantitative performance metrics computation shows that the proposed method for shadow detection and removal is better than other state-of-the-art methods.

关键词： Shadow detection Shadow removal dual tree complex wavelet transform Standard deviation

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dual tree complex wavelet transform and Bayesian estimation based denoising of Poission-corrupted X-ray Images

Dual tree complex wavelet transform and Bayesian estimation ...

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4th International Conference on Intelligent Control and Information Processing (ICICIP)

作者： Du, Lingyan Wen, Yuqiao Ma, Jiang Sichuan Univ Sci & Engn Coll Automat & Elect Informat Engn Chengdu Peoples R China

ISBN: (纸本)9781467362498;9781467362481

Degradation of digital X-ray medical image is usually caused by effects of X-ray scattering and electrical noise etc. But the Quantum noise is the main noise source of X-ray medical images and can be modeled by a Poisson process. An algorithm for image restoration in the presence of Poisson noise is presented in this paper. The approach is based on dual tree complex wavelet transform and Bayesian estimation, the threshold function is derived using Bayesian estimation theory. Compared with the traditional discrete wavelet transform, the method based on dual tree complex wavelet transform and Bayesian estimation has the properties of approximate shift invariance and more directionality, and better results were obtained by using the proposed algorithm in terms of PSNR. The method allows fast and efficient denoising of images obtained under low X-ray radiation conditions.

关键词： Poisson dual tree complex wavelet transform Bayesian estimation X-ray image denoising

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Robust and Sparse dual tree complex wavelet transform-Based Twin Support Vector Regression for 5G InH and V2I Communications

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WIRELESS PERSONAL COMMUNICATIONS 2023年第3期128卷 1603-1630页

作者： Charrada, Anis Samet, Abdelaziz Univ Carthage Tunisia Polytech Sch SERCOM Box 743-2078 La Marsa Tunisia CRM Sci & Technol Def Lab Aouina 2045 Tunisia INRS EMT Ctr 800 Gauchetiere WSuite 6900 Montreal PQ H5A 1K6 Canada

In this article, a robust and sparse Twin Support Vector Regression based on dual tree complex Discrete wavelet transform algorithm is proposed and applied to dense 5G InH (Indoor Hotspot) LOS (Line-of-Sight) multipath communications for several frequencies 28, 38, 60 and 73-GHz. Moreover, PDF (Probability Distribution Function) and large-scale propagation parameters are determined in terms of free space path loss value (FSPL), standard deviation of Shadow Factor (SF) and PLE (Path Loss Exponent) for each dense InH scenario under consideration according to the Close-In (CI) free space reference distance path loss model. Furthermore, large-scale analysis for 5G outdoor Vehicular-to-Infrastructure (V2I) NLOS communications are investigated in terms of measured path loss values (FSPL, PLE, SF, PDF) for mmWave frequencies 28, 38, 60 and 73 GHz. Additionally, the outdoor V2I communications scenarios based on two types of horn antennas (22 deg/15 dBi and 07 deg/25 dBi) and a constantly aligning mechanism between Tx and Rx antenna beams are considered and evaluated.

关键词： mmWave dual tree complex wavelet transform V2I Indoor hotspot Path loss Close-in model

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