Yanming Wang^1,2,3, Kebin Jia^1,2,3,*, Pengyu Liu^1,2,3

Journal on Internet of Things, Vol.2, No.3, pp. 109-120, 2020, DOI:10.32604/jiot.2020.010138

Abstract With the global climate change, the high-altitude detection is more and more important in the climate prediction, and the input-output characteristic curve of the air pressure sensor is offset due to the interference of the tested object and the environment under test, and the nonlinear error is generated. Aiming at the difficulty of nonlinear correction of pressure sensor and the low accuracy of correction results, depth neural network model was established based on wavelet function, and Levenberg-Marquardt algorithm is used to update network parameters to realize the nonlinear correction of pressure sensor. The experimental results show that compared with the… More >

Zequn Wang, Rui Jiao, Huiping Jiang^*

Journal of New Media, Vol.2, No.3, pp. 121-130, 2020, DOI:10.32604/jnm.2020.010674

Abstract With the continuous development of the computer, people's requirements for computers are also getting more and more, so the brain-computer interface system (BCI) has become an essential part of computer research. Emotion recognition is an important task for the computer to understand social status in BCI. Affective computing (AC) aims to develop the model of emotions and advance the affective intelligence of computers. There are various emotion recognition approaches. The method based on electroencephalogram (EEG) is more reliable because it is higher in accuracy and more objective in evaluation than other external appearance clues such as emotion expression and gesture.… More >

Zhenhua Guo^1,2, Lixin Zhang^1,*, Xue Hu¹, Huanmei Chen²

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 625-630, 2020, DOI:10.32604/iasc.2020.013941

Abstract Wind speed prediction is an important part of the wind farm management and wind power grid connection. Having accurate prediction of short-term wind speed is the basis for predicting wind power. This paper proposes a short-term wind speed prediction strategy based on the wavelet analysis and the multilayer perceptual neural network for the Dabancheng area, in China. Four wavelet neural network models using the Morlet function as the wavelet basis function were developed to forecast short-term wind speed in January, April, July, and October. Predicted wind speed was compared across the four models using the mean square error and regression.… More >

Machiraju Jayalakshmi^{1, *}, S. Nagaraja Rao²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1081-1096, 2020, DOI:10.32604/cmc.2020.011710

Abstract In recent years, the development in the field of computer-aided diagnosis (CAD) has increased rapidly. Many traditional machine learning algorithms have been proposed for identifying the pathological brain using magnetic resonance images. The existing algorithms have drawbacks with respect to their accuracy, efficiency, and limited learning processes. To address these issues, we propose a pathological brain tumour detection method that utilizes the Weiner filter to improve the image contrast, 2D- discrete wavelet transformation (2D-DWT) to extract the features, probabilistic principal component analysis (PPCA) and linear discriminant analysis (LDA) to normalize and reduce the features, and a feed-forward neural network (FNN)… More >

S. Deivalakshmi^*, P. Palanisamy¹, X. Z. Gao²

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 459-471, 2019, DOI:10.31209/2018.100000001

Abstract The main aim of this paper is to propose a new technique for enhancing the contrast of dark images using Dynamic Stochastic Resonance (DSR) and Multi Wavelet Transform (MWT), which is computationally more efficient than the conventional methods. In the work, for enhancing the contrast of dark images, the intrinsic noise (darkness) of dark images has been used. The proposed MWT-based DSR scheme (MWT-DSR) can yield better performances in terms of visual information and color preservation than already reported techniques. The desired output response is validated by the Relative Contrast Enhancement Factor (F), Perceptual Quality Measures (PQM) and Color Enhancement… More >

Nan Pan¹, Yi Liu², Dilin Pan², Junbing Qian¹, Gang Li³

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 359-366, 2019, DOI:10.31209/2019.100000097

Abstract It will face a lot of problems when using existing image-processing and 3D scanning methods to do the similarity analysis of the line traces, therefore, an effective comparison algorithm is put forward for the purpose of making effective trace analysis and infer the criminal tools. The proposed algorithm applies wavelet decomposition to the line trace 1-D detection signals to partially reduce background noises. After that, the sequence comparison strategy based on wavelet domain DTW is employed to do trace feature similarity matching. Finally, using linear regression machine learning algorithm based on gradient descent method to do constant iteration. The experiment… More >

Yunxiang Zhao¹, Jinyong Cheng^{1, *}, Ping Zhang¹, Xueping Peng²

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1615-1628, 2020, DOI:10.32604/cmc.2020.09938

Abstract Atrial fibrillation is the most common persistent form of arrhythmia. A method based on wavelet transform combined with deep convolutional neural network is applied for automatic classification of electrocardiograms. Since the ECG signal is easily inferred, the ECG signal is decomposed into 9 kinds of subsignals with different frequency scales by wavelet function, and then wavelet reconstruction is carried out after segmented filtering to eliminate the influence of noise. A 24-layer convolution neural network is used to extract the hierarchical features by convolution kernels of different sizes, and finally the softmax classifier is used to classify them. This paper applies… More >

T. Jayasree^1,*, R. Prem Ananth²

Sound & Vibration, Vol.54, No.1, pp. 57-74, 2020, DOI:10.32604/sv.2020.08573

Abstract Vehicles generate dissimilar sound patterns under different working environments. These generated sound patterns signify the condition of the engines, which in turn is used for diagnosing various faults. In this paper, the sound signals produced by motorcycles are analyzed to locate various faults. The important attributes are extracted from the generated sound signals based on time, frequency and wavelet domains which clearly describe the statistical behavior of the signals. Further, various types of faults are classified using the Extreme Learning Machine (ELM) classifier from the extracted features. Moreover, the improved classification performance is obtained by the combination of feature sets… More >

Mengling Zou¹, Zhengxuan Liu², Xianyi Chen^{3, *}

Journal on Big Data, Vol.1, No.3, pp. 151-158, 2019, DOI:10.32604/jbd.2019.09057

Abstract Image encryption (IE) is a very useful and popular technology to protect the privacy of users. Most algorithms usually encrypt the original image into an image similar to texture or noise, but texture and noise are an obvious visual indication that the image has been encrypted, which is more likely to cause the attacks of enemy. To overcome this shortcoming, many image encryption systems, which convert the original image into a carrier image with visual significance have been proposed. However, the generated cryptographic image still has texture features. In line with the idea of improving the visual quality of the… More >

Satya Prakash Yadav^{1, *}, Sachin Yadav²

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 303-321, 2020, DOI:10.32604/cmes.2020.08459

Abstract This paper presents a low intricate, profoundly energy effective MRI Images combination intended for remote visual sensor frameworks which leads to improved understanding and implementation of treatment; especially for radiology. This is done by combining the original picture which leads to a significant reduction in the computation time and frequency. The proposed technique conquers the calculation and energy impediment of low power tools and is examined as far as picture quality and energy is concerned. Reenactments are performed utilizing MATLAB 2018a, to quantify the resultant vitality investment funds and the reproduction results show that the proposed calculation is very quick… More >