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Random-projection-based dimensionality reduction and decision fusion for hyperspectral target detection
2011
2011 IEEE International Geoscience and Remote Sensing Symposium
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Random projection is attractive in this task because it is data independent and computationally more efficient than other widely-used dimensionality-reduction methods, such as principal component analysis ...
Experimental results reveal that dimensionality reduction based on random projections yields improved target detection after decision fusion across multiple instances of the projections. ...
Random projection (RP) is a computationally efficient, data-independent method for dimensionality reduction [1] . ...
doi:10.1109/igarss.2011.6049468
dblp:conf/igarss/DuFM11
fatcat:o7bkcanh55acxltdp7x77iz5my
Efficient Compressive Multi-Focus Image Fusion
2014
Journal of Computer and Communications
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Experimental results on common used testing data demonstrate the effectiveness of the proposed method. ...
However, the traditional clarity measures are not designed for compressive imaging measurements which are maps of source sense with random or likely random measurements matrix. ...
Conclusion In this work, we present a novel image fusion scheme about efficient compressive multi-focus image fusion. ...
doi:10.4236/jcc.2014.29011
fatcat:raaodpojezbtpnemicv66dkcja
Leakage Detection in Pipeline Network Based on Random Forest Fusion
2018
DEStech Transactions on Engineering and Technology Research
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The random forest data mining method is used to determine the characteristic parameters as the input parameters of random forest fusion to classify the working conditions of the pipeline network. ...
Firstly, the theoretical background of random forest and independent component analysis was introduced. The ICA was used to reducing noise of the negative pressure wave signal and the flow signal. ...
It is a method to do data mining of the characteristics, by this way, it could reduce the complexity of the algorithm input data set and improve the efficiency by using characteristics mined form the random ...
doi:10.12783/dtetr/amme2017/19517
fatcat:dr57js2rmfdrfe7kswms2i5cpm
A new adaptive compressed sensing algorithm for Wireless Sensor Networks
2010
IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS
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In this paper, proposed the spatial correlation node data compression and fusion algorithm based on the theory of compressed sensing. ...
Firstly, make signal node random projection based on time correlation, then, for random routing instability and network transmission of data fusion technology reconstruction energy effects, proposed the ...
associated with the sparse matrix based (such as a random matrix) for sensing data observation and coding, which is far less than the original length of the encoded signal. ...
doi:10.1109/icosp.2010.5657045
fatcat:bbxblcaoxjh4dlv22cnor2xk4y
Random weighting estimation for fusion of multi-dimensional position data
2010
Information Sciences
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Using the random weighting estimations from each single sensor, an optimization theory is established for optimal fusion of multi-sensor position data. ...
This paper adopts the concept of random weighting estimation to multi-sensor data fusion. ...
Nevertheless, there has been little research to use random weighting estimation for multi-sensor data fusion. ...
doi:10.1016/j.ins.2010.08.023
fatcat:sglbfeaktbe6temi6p3sxpyvtq
A method for co-existing heterogeneous IoT environments based on compressive sensing
2016
2016 18th International Conference on Advanced Communication Technology (ICACT)
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Then, an efficient cluster-sparse reconstruction algorithm is proposed for in-network compression aiming at more accurate data reconstruction and lower energy efficiency. ...
Then, a CS-based framework is proposed for IoT, in which the hub nodes measure, transmit, and store the sampled data into the fusion center. ...
The CS theory typically requires the projection matrix to be random, though in practice researchers have often found that the same idea can be used in other conventional sampling scenarios. ...
doi:10.1109/icact.2016.7423329
fatcat:geslcgqj5rhwxlyousui7ib3om
Wireless Sensor Networks Data Processing Summary Based on Compressive Sensing
2014
Sensors & Transducers
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As a newly proposed theory, compressive sensing (CS) is commonly used in signal processing area. ...
fusion, signal acquisition, signal routing transmission, and signal reconstruction. ...
Therefore, the authors propose that compressed sensing technology is used in WSNs data fusion. ...
doaj:00a3270288c548a0ba209d8759716f6c
fatcat:vcdy4gnsb5b3bjoaxivhhcob4q
Research on Remote Sensing Image Fusion Based on Compressive Sensing Algorithm
2018
Journal of Computers
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In this paper, we present an efficient remote sensing fusion method based on compressive sensing. ...
Then the sparse results are compressed through a measurement matrix and different fusion coefficients are chosen on each component of the compressed images. ...
The process is expressed as:
Measurement Matrix Common measurement matrices include Gaussian random matrix, random Bernoulli matrix, partially orthogonal matrix, Hadamard random matrix, sparse random ...
doi:10.17706/jcp.13.5.519-526
fatcat:vmun6dfdq5daxjqyf4qara3g3u
IMAGE FUSION AND RECOGNITION BASED ON COMPRESSED SENSING THEORY
2015
International Journal on Smart Sensing and Intelligent Systems
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As the compressed sensing theory can offer a better performance than Nyquist sampling theorem when dealing with large amounts of data, it becomes very popular for image fusion and target recognition in ...
Moreover, a recognition algorithm in compressed sensing was also studied, which obtained a sample matrix using preprocessing based on a wavelet transform, calculated the approximate coefficient by orthogonal ...
Through using a observation matrix to measure the original data, fusing the observation data directly, and reconstructing the fusion data, it obtains a fusion image. ...
doi:10.21307/ijssis-2017-753
fatcat:rnw27kcptracvag2ztxhrdyxjq
Product Design Method Based on Data Fusion and Transmission Based on Multimode Sensor
2022
Mobile Information Systems
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And through the research on multimodal data fusion algorithm, the design method based on multimodal sensor data fusion and transmission technology is designed and practiced, and compared with the traditional ...
Therefore, this paper integrates multimodal sensor data fusion and transmission into product design. ...
Assuming that there are two groups of variables, using (p × 1) random vector X (1) to represent the first set of p random variables. ...
doi:10.1155/2022/5709786
fatcat:vc4aeg5nbvhjxcj2wxzhxpjwpe
Robust Detection of Random Events with Spatially Correlated Data in Wireless Sensor Networks via Distributed Compressive Sensing
[article]
2017
arXiv
pre-print
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Exploiting the sparsity structure of the covariance matrix, we develop a robust nonparametric detector to detect the presence of the random event using a compressed version of the data collected at the ...
In this paper, we exploit the theory of compressive sensing to perform detection of a random source in a dense sensor network. ...
Using the sample estimate of the covariance matrix of compressed data with limited samples, we compute a decision statistic in terms of the covariance matrix of uncompressed data. ...
arXiv:1707.08208v1
fatcat:tcchnjx7pbaf5dalybyq5sk3ia
Fusion in the Context of Information Theory
[chapter]
2012
Distributed Sensor Networks, Second Edition
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In particular, we discuss how Bayesian methods for distributed data fusion can be interpreted from the point of view information theory. ...
fusion. ...
With respect to data fusion, the early research in the fields of information theory and fusion proceeded somewhat independently. ...
doi:10.1201/b12991-27
fatcat:7i2plfyohfcrlbzn5nlmnpkeda
Fusion in the Context of Information Theory
[chapter]
2004
Distributed Sensor Networks
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In particular, we discuss how Bayesian methods for distributed data fusion can be interpreted from the point of view information theory. ...
fusion. ...
With respect to data fusion, the early research in the fields of information theory and fusion proceeded somewhat independently. ...
doi:10.1201/9780203487068.ch22
fatcat:pkybumygdfcbnccb5y7fbgdq4i
Research on Data Fusion Technology Based on Compressed Sensing
2016
International Journal of Online Engineering (iJOE)
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First introduce a traditional compressed sensing data fusion technique, and aiming at the shortcoming of traditional method, a compressed sensing data fusion technology based on temporal-spatial correlation ...
Then modeling on the proposed data fusion technique, improve the CS reconstruction algorithm and present the iterative threshold reconstruction algorithm based on temporal-spatial correlation. ...
The compressed sensing data fusion technology based on temporal-spatial correlation makes full use of the temporal-spatial correlation of WSN data, and combines random routing, sampling and compression ...
doi:10.3991/ijoe.v12i08.5646
fatcat:umvfbl2syfhnlnxnqdxcxkp5hm
Fusion of Infrared and Visible Images Using Nonsubsampled Shearlet Transform and Block-based Random Image Sampling
2016
Revista Técnica de la Facultad de Ingeniería Universidad del Zulia
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The experiments are carried out on five pairs of infrared and visible images using five traditional fusion methods to verify the effectiveness and efficiency of the proposed method and by comparing the ...
This paper presents a novel image fusion method based on nonsubsampled shearlet transform (NSST) and block-based random image sampling for infrared and visible images. ...
There are many matrices meeting the condition including Gaussian random matrix, Bernoulli matrix and Hadamard matrix, in which Gaussian random matrix is used in this work. ...
doi:10.21311/001.39.7.42
fatcat:3kesocryqzaelnqvrqx2cx65bu
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