The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
For vary interval data serial, the data serial is interpolaed by Chaos-dynamic neural network method. combining the chaotic feature of data serial, the method of Wavelet denoising of data serial is improved, and the noise is effectively filtered, while the variation trend and data character of initial data can well be retained, and real signal (abnormal value) can be reserved. So these treatment methods...
This article directs at coal manufacturing cost factors applying support vector machine (SVM) theory, it establishes forecasting model of coal manufacturing cost using wavelet neural network after reducting attribute of influence factors, in order to forecast the coal manufacturing cost effectively.
A new approach to classification of non-stationary power signals based on adaptive wavelet has been considered. This paper proposes a model for non-stationary power signal disturbance classification using adaptive wavelet networks (AWN). A AWN is a combination of two sub-networks consisting of a wavelet layer and adaptive probabilistic network. The AWN has the capability of automatic adjustment of...
A hybrid particle swarm optimization (PSO)-based wavelet neural network (WNN) for Video OCR is presented in this paper. Video OCR is an important task towards enabling automatic content-based retrieval of digital video databases. However, since text is often displayed against a complex background, its detection and extraction is a challenging problem. In this paper, wavelet transformation is done...
In this work, we proposed a novel authentication system based on facial features. The proposed method is based on PCA and LDA for feature extraction, these extracted features are combined using wavelet fusion. In this work we use neural networks to classify extracted features of faces. The proposed method consists of six steps: i) Extraction of images from the database, ii) Preprocessing, iii) Feature...
The advantages of wavelets and their promising features in various application have attracted a lot of interest and effort in recent years. In this article, the notion of two-directional biorthogonal finitely supported trivariate wavelet packets with multi-scale is developed. Their properties is investigated by virtue of algebra theory, time-frequency analysis method and functional analysis method...
Most wavelet filters that constructed based on Daubechies compactly-supported wavelet construction theory have nonlinear phase and irrational number coefficients. Nonlinear phase may cause distortion in image processing, and irrational filter coefficients will cause much inconvenience for wavelet applications on computer, especially for embedded processor applications. With thought of the theory of...
Recent advances in neuroimaging demonstrate the potential use of functional near infrared spectroscopy (fNIRS) in the field of brain machine interface. An fNIRS uses light in the near infrared range to measure brain surface hemoglobin concentrations to determine a neural activity. The current study presents our empirical results in realizing fNIRS - BCI system. We analyze the hemodynamic responses...
Medical Diagnosis is the utmost need of an hour. Gestational Diabetics in women represents the second leading cause of yielding children born with birth defects. The ultrasound images are usually low in resolution making diagnosis difficult. Specialized tools are required to assist the medical experts to categorize and diagnose diseases to accuracy. If the anomalies in the ultrasound images are detected...
We have created and analyzed an elicited emotional database consisting of 340 emotional speech samples under four different emotions neutral, happy, sad and anger. Malayalam (one of the south Indian languages) was used for the experiment. Daubechies8 wavelet was used for feature extraction and artificial neural network was used for pattern recognition. An overall recognition accuracy of 72.055% obtained...
Aimed at the intrusion behaviors are characterized with uncertainty, complexity, diversity and dynamic tendency and the advantages of wavelet neural network (WNN), an intrusion detection method based on WNN is presented in this paper. Moreover, we adopt a algorithm of reduce the number of the wavelet basic function by analysis the sparseness property of sample data which can optimize the wavelet network...
This paper suggests a novel method named DOSCWTRBFN based on radial basis function neural network (RBFN) with direct orthogonal signal correction (DOSC) and wavelet transform (WT) as a pre-processing tool for the simultaneous spectrophotometric determination of Mn(II), Zn(II), Co(II) and Cd(II). In this case, by optimization, the number of DOSC components, tolerance factor, wavelet function, decomposition...
A time-series prediction model using a Bilinear Recurrent Neural Network (BRNN) is proposed in this paper. The BRNN model used in this paper is the Multiresolution architecture with an adaptive training mode. The Multiresolution Bilinear Recurrent Neural Network (MBRNN) is based on the BLRNN that has been proven to have robust abilities in modeling and predicting time series. The proposed MBRNN-based...
Multi-sensors information fusion (MSIF) technology, is being widely applied to various fields, particularly, the modern military field. In order to enhance the capability of ship chemical defense support in the future informationalization sea warfare, a review of the study and application about MSIF technology in naval ships chemical detection (NSCD) field is researched, the model of NSCD system based...
In this paper, we propose some technologies of multi-biometric feature identification, and present a framework of biometric identification system. The contributions of this paper include the following aspects: (1) the information of biological features are prevented from being forged or modified in network transmission by using a scrambling encryption algorithm of Semi-Fragile Watermarking(SFW) which...
The motor is the workhorse of industry. The control and identification of induction motor with artificial intelligence is the key point for high performance electrical drives. A novel architecture of nonlinear autoregressive moving average (NARMA) model based on wavelet neural networks (WNN) is presented for enhancing the performance of induction motor. The Akaikepsilas final predication error (AFPE)...
A recurrent wavelet neural network (RWNN) controller is proposed in this study to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive to track periodic reference trajectories. First, the dynamic model of the PMLSM drive system is derived. Next, an RWNN controller is proposed to control the PMLSM. Moreover, the connective weights, translations and dilations of the RWNN...
Curved surface renewable solar cell is applied to provide a near space airshippsilas energy system the power to drive the high altitude electromotor and propeller in a long term. The solar flux incident on the solar cell is calculated through integral transform and some revised correlations from tilted surface solar radiation flux calculations. In view of the solar radiation flux and the wind speed...
The aim of this paper is to propose a method for the detection of faults in industrial systems, such as electrical machines and drives, through on-line monitoring system. Early fault detection, which reduces the possibility of catastrophic damage, is possible by comparing the measured signals with a database that contains characteristic signals for machines operating with and without faulty conditions...
In this paper, two modifications for speaker recognition are presented. The goal of de-noising is to remove the noise and to remain as much as possible the important features. Recently, signal de-noising using nonlinear processing, for example, wavelet transformation have become increasingly popular. First, for threshold in the wavelet domain, a semi-soft threshold function that showed the advantages...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.