Big data contains huge data value, can effectively promote the development of university information;However, there are many difficulties in the application of big data in multi-sensor dataprocessing. In view of the ...
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With the rapid development of China's economy, people's demand for electricity is increasing, so that the power grid will generate a large amount of data information in the actual operation, and the smart grid...
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In this work, a report on different signal decomposition techniques (time-frequency TF) applied to power quality (PQ) events are provided. In a system with hybrid renewable sources, nonlinear load points and capacitor...
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For many applications, such as targeted advertising and content recommendation, knowing users' traits and interests is a prerequisite. User profiling is a helpful approach for this purpose. However, current method...
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ISBN:
(纸本)9781538609699
For many applications, such as targeted advertising and content recommendation, knowing users' traits and interests is a prerequisite. User profiling is a helpful approach for this purpose. However, current methods, i.e. self-reporting, web-activity monitoring and social media mining are either intrusive or require data over long periods of time. Recently, there is growing evidence in cognitive science that a variety of users' profile is significantly correlated with eye-tracking data. A novel just-in-time implicit profiling method, Eye-2-I, which learns the user's demographic and personality traits from the eye-tracking data while the user is watching videos is proposed. Although seemingly conspicuous by closely monitoring the user's eye behaviors, the proposed method is unobtrusive and privacy-preserving owing to its unique combination of speed and implicitness. As a proof-of-concept, the proposed method is evaluated in a user study with 51 subjects.
We present a scheme for combining fuzzy c-means clustering with generalized regression neural network for improving its pattern classification efficiency. The membership grades of data points produced by fuzzy c-means...
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ISBN:
(纸本)9781479959914
We present a scheme for combining fuzzy c-means clustering with generalized regression neural network for improving its pattern classification efficiency. The membership grades of data points produced by fuzzy c-means clustering have been used to define weights for data points in the feature space according a logarithmic measure of uncertainty similar to the Shannon's entropy. The method improves classification results from 1% to 17% for 9 data sets analyzed here.
The main concern for many applications (for example, for Coriolis Mass Flow Meter signalprocessing in two-phase flow conditions) is to track several domain poles of signals with minimum delay. The Matrix Pencil metho...
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ISBN:
(纸本)9781538605219
The main concern for many applications (for example, for Coriolis Mass Flow Meter signalprocessing in two-phase flow conditions) is to track several domain poles of signals with minimum delay. The Matrix Pencil method (MPM) estimates the signal as a sum of complex exponentials. Creating a computationally efficient moving MPM implementation is of a high interest. The most computationally expensive step of the classical MPM is to calculate the singular value decomposition (SVD) of a matrix composed from the signal samples. When a new data point enters the data window, this matrix changes only slightly, and it is reasonable to find its SVD not directly but using the SVD of the old matrix and a low-rank SVD modification procedure. In this paper a well-known SVD modification procedure is adapted for MPM and a recursive version of MPM is proposed. The amended method is validated by numerical examples and is faster than the original suggesting it may be feasible to track signal parameters on-line. The errors accumulating over time due to the recursive calculation require the recursive MPM to be restarted periodically.
Hand gesture recognition refers to identification of various hand postures which interprets the signs of non verbal communication. It finds various applications like Sign Language Recognition (SLR), Human Computer Int...
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Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundanc...
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Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.
For the purpose of fault diagnosis, a synthesis signalprocessing method was employed In certain mechanical fault diagnosis system. Several useful technologies were adopted in the system, such as fuzzy theory correlat...
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ISBN:
(纸本)7800033910
For the purpose of fault diagnosis, a synthesis signalprocessing method was employed In certain mechanical fault diagnosis system. Several useful technologies were adopted in the system, such as fuzzy theory correlation analysis, data base and parameter identification technology The computer program was built based on these technologies The principle and the steps used In this system can be used in other similar fault diagnosis system as well.
ECG signals appear more and more frequently in people's lives. Through ECG signals, we can learn some of the most basic physiological information of the human body. Through the physiological information, we can an...
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