Faculty Opinions recommendation of ATTED-II in 2018: A Plant Coexpression Database Based on Investigation of the Statistical Property of the Mutual Rank Index.

The traditional Otsu threshold algorithm is not a good method for processing the real images because of complex shape and unbalanced distribution. To solve this problem, the paper uses the thinking of Otsu’s method for reference, introduces a threshold segmentation algorithm based on histogram statistical property. In addition, the paper draws a comparison between the new algorithm and Otsu’s algorithm. Experimental results show that the new algorithm can get better segmentation effect than that of Otsu’s method when the gray-level distribution of the background follows normal distribution approximatively, and the target region is less than the background region.

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Statistical property of the Chandler wobble excitation function

Chinese Science Bulletin ◽

10.1007/bf03183420 ◽

2004 ◽

Vol 49 (22) ◽

pp. 2348-2353

Author(s):

Dechun Liao ◽

Xinhao Liao ◽

Yonghong Zhou

Keyword(s):

Excitation Function ◽

Chandler Wobble ◽

Statistical Property

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How to Avoid LEM Cycles in Mutual Rank Probability Relations

Advances in Intelligent and Soft Computing - Combining Soft Computing and Statistical Methods in Data Analysis ◽

10.1007/978-3-642-14746-3_20 ◽

2010 ◽

pp. 155-163

Author(s):

K. De Loof ◽

B. De Baets ◽

H. De Meyer

Keyword(s):

Mutual Rank

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Stationary Time Statistical Property of Ionospheric Clutter in High-Frequency Surface-Wave Radar

Journal of Electrical and Computer Engineering ◽

10.1155/2019/2450191 ◽

2019 ◽

Vol 2019 ◽

pp. 1-6

Author(s):

Shang Shang ◽

Kangning He ◽

Zhaobin Wang ◽

Xuguang Yang

Keyword(s):

Surface Wave ◽

High Frequency ◽

Real Data ◽

Radar System ◽

Detection Performance ◽

Frequency Selection ◽

Statistical Property ◽

Stationary Time ◽

Wave Radar

In HFSWR (high-frequency surface-wave radar) system, the detection performance is impacted seriously by ionospheric clutter. Frequency selection is an effective method to avoid the effect of ionospheric clutter. The key to the method is the stationarity of ionospheric clutter over a period of time. This paper mainly researches the stationary time statistical property of the ionospheric clutter. A large number of real data including ionospheric clutter in HFSWR are processed and analyzed. It shows that ionospheric clutter in HFSWR has the characteristics of approximate stationarity within a period of time.

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