Laser Speckle in Multimode Waveguides for Random Projections in Compressive Sensing and Reservoir Computing

2019 ◽  
Author(s):  
G. A. Sefler ◽  
U. Paudel ◽  
T. J. Shaw ◽  
D. Monahan ◽  
A. C. Scofield ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Laser Speckle ◽  
Random Projections ◽  
Reservoir Computing ◽  
Multimode Waveguides

Recent results using laser speckle in multimode waveguides for random projections

2019 ◽  
Author(s):  
Adam C. Scofield ◽  
George Sefler ◽  
Justin Shaw ◽  
George Valley
Keyword(s):  
Laser Speckle ◽  
Random Projections ◽  
Multimode Waveguides

GHz-Band RF Receiver and Spectrometer Based on Laser Speckle in Multimode Waveguides

2018 ◽  
Author(s):  
Adam C. Scofield ◽  
George A. Sefler ◽  
T. Justin Shaw ◽  
Andrew D. Stapleton ◽  
George C. Valley
Keyword(s):  
Laser Speckle ◽  
Rf Receiver ◽  
Multimode Waveguides

scholarly journals A Compressive Sensing Model for Speeding Up Text Classification

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Kelin Shen ◽  
Peinan Hao ◽  
Ran Li
Keyword(s):  
Compressive Sensing ◽  
Text Classification ◽  
Feature Space ◽  
High Dimensionality ◽  
Random Projections ◽  
Text Documents ◽  
Sensing Model ◽  
Speed Up ◽  
Text Features ◽  
Time And Space Complexity

Text classification plays an important role in various applications of big data by automatically classifying massive text documents. However, high dimensionality and sparsity of text features have presented a challenge to efficient classification. In this paper, we propose a compressive sensing- (CS-) based model to speed up text classification. Using CS to reduce the size of feature space, our model has a low time and space complexity while training a text classifier, and the restricted isometry property (RIP) of CS ensures that pairwise distances between text features can be well preserved in the process of dimensionality reduction. In particular, by structural random matrices (SRMs), CS is free from computation and memory limitations in the construction of random projections. Experimental results demonstrate that CS effectively accelerates the text classification while hardly causing any accuracy loss.

Laser Speckle Mitigation Through Substandard Compressive Sensing

2020 ◽  
Author(s):  
Derek Burrell ◽  
Bruce Berry ◽  
Mark Spencer ◽  
Ronald Driggers
Keyword(s):  
Compressive Sensing ◽  
Laser Speckle

Laser speckle reduction based on compressive sensing and edge detection

2013 ◽  
Author(s):  
Dong-hai Wen ◽  
Yue-song Jiang ◽  
Hou-qiang Hua ◽  
Rong Yu ◽  
Qian Gao ◽  
...  
Keyword(s):  
Edge Detection ◽  
Compressive Sensing ◽  
Laser Speckle ◽  
Speckle Reduction

Compressive Sensing for Wireless Networks

2009 ◽  
Author(s):  
Zhu Han ◽  
Husheng Li ◽  
Wotao Yin
Keyword(s):  
Wireless Networks ◽  
Compressive Sensing
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