Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automate...

In recent years, the wavelet transform emerged in the field of image/signal processing as an alternative to the well-known Fourier Transform (FT) and its related transforms, namely, the Discrete Cosine Transform (DCT) and the Discrete Sine Transform (DST). In the Fourier theory, a signal (an image is considered as a finite 2-D signal) is expressed as a sum, theoretically infinite, of sines and ...

This study develops an automated method capable of detecting notches in isotropic plates. Laser ultrasonic techniques are used to generate and detect Lamb waves in perfect and notched plates. These signals are first transformed into the time-frequency domain using a short time Fourier transform (STFT) and subsequently into the group velocity-frequency domain. Finally, the notch is located with ...

In this paper, we propose a musical onset detection method, with reference to polyphonic piano music. The solution proposed consists of an onset detection algorithm based on Short-Time Fourier Transform (STFT) and Non-Negative Matrix Factorization (NMF). This method operates on a frame-by-frame basis and exploits a suitable binary time-frequency representation of the audio signal. To validate t...

Damage to the surface of railway wheels and rails commonly occurs in most railways and, if not detected at an early stage, can result in rapid deterioration and possible failure incurring high maintenance costs. If detected at an early stage these maintenance costs can be minimised. This paper presents an investigation into the use of time-frequency analysis of vibrations in railway vehicles fo...

In state-of-the-art single channel short-time Fourier transform (STFT) based speech enhancement algorithms only the amplitude of the noisy speech signal is improved, but its phase is left unchanged. It is commonly assumed that the noisy phase is the best estimate of the clean phase available. While using the noisy phase is indeed optimal under certain statistical assumptions, in this paper we s...

This paper provides a solution for robust speech detection that can be applied across a variety of tasks. The solution is based on an algorithm that performs non-parametric estimation of the background noise spectrum using minimum statistics of the smoothed short-time Fourier transform (STFT). It will be shown that the new algorithm can operate effectively under varying signal-to-noise ratios. ...

This paper proposes a novel pavement transverse crack detection model based on time–frequency analysis and convolutional neural networks. The accelerometer smartphone installed in the vehicle collect vibration response between wheel road, such as cracks, manholes, normal pavement. Since original signal can only contain one-dimensional domain (time–acceleration). Time–frequency analysis, includi...

OBJECTIVE The main goal of this study was to develop a real-time detection algorithm of movement-related EEG changes for the naïve subjects with a very small amount of training data. Such an algorithm is vital for the realization of brain-computer interface. METHODS The target algorithm developed in this study was based on the wavelet decomposition neural network (WDNN). Surface Laplacian EEG...