AIMC Topic: Wavelet Analysis

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Multi-Sensor Fusion by CWT-PARAFAC-IPSO-SVM for Intelligent Mechanical Fault Diagnosis.

Sensors (Basel, Switzerland)
A new method of multi-sensor signal analysis for fault diagnosis of centrifugal pump based on parallel factor analysis (PARAFAC) and support vector machine (SVM) is proposed. The single-channel vibration signal is analyzed by Continuous Wavelet Trans...

A Novel Bitcoin and Gold Prices Prediction Method Using an LSTM-P Neural Network Model.

Computational intelligence and neuroscience
As a result of the fast growth of financial technology and artificial intelligence around the world, quantitative algorithms are now being employed in many classic futures and stock trading, as well as hot digital currency trades, among other applica...

An Approach to Intelligent Fault Diagnosis of Cryocooler Using Time-Frequency Image and CNN.

Computational intelligence and neuroscience
Cryocooler plays an essential role in the field of infrared remote sensing. Linear compressor, as the power component of the cryocooler, will directly affect the normal operation and performance of the detector if there is a fault. Therefore, the int...

Recognition of Protein Network for Bioinformatics Knowledge Analysis Using Support Vector Machine.

BioMed research international
Protein is the material foundation of living things, and it directly takes part in and runs the process of living things itself. Predicting protein complexes helps us understand the structure and function of complexes, and it is an important foundati...

Time-Frequency Analysis of Scalp EEG With Hilbert-Huang Transform and Deep Learning.

IEEE journal of biomedical and health informatics
Electroencephalography (EEG) is a brain imaging approach that has been widely used in neuroscience and clinical settings. The conventional EEG analyses usually require pre-defined frequency bands when characterizing neural oscillations and extracting...

Sensor Fault Diagnostics Using Physics-Informed Transfer Learning Framework.

Sensors (Basel, Switzerland)
The field of smart health monitoring, intelligent fault detection and diagnosis is expanding dramatically in order to maintain successful operation in many engineering applications. Considering possible fault scenarios that can occur in a system, ind...

Application of a Hybrid Model of Big Data and BP Network on Fault Diagnosis Strategy for Microgrid.

Computational intelligence and neuroscience
Aiming at the characteristics of timely transmission, rapid update, and large magnitude of microgrid data, based on the large data samples generated by microgrid operation, a fault diagnosis and analysis method of microgrid systems supported by big d...

Classification of breast cancer with deep learning from noisy images using wavelet transform.

Biomedizinische Technik. Biomedical engineering
In this study, breast cancer classification as benign or malignant was made using images obtained by histopathological procedures, one of the medical imaging techniques. First of all, different noise types and several intensities were added to the im...

A Time Series Forecasting Approach Based on Nonlinear Spiking Neural Systems.

International journal of neural systems
Nonlinear spiking neural P (NSNP) systems are a recently developed theoretical model, which is abstracted by nonlinear spiking mechanism of biological neurons. NSNP systems have a nonlinear structure and the potential to describe nonlinear dynamic sy...

The Identification of ECG Signals Using WT-UKF and IPSO-SVM.

Sensors (Basel, Switzerland)
The biometric identification method is a current research hotspot in the pattern recognition field. Due to the advantages of electrocardiogram (ECG) signals, which are difficult to replicate and easy to obtain, ECG-based identity identification has b...