Efficient Training of MLP with Training Step Rate Estimation

2000 ◽  
pp. 21-26
Author(s):  
Vladimir Golovko ◽  
Yury Savitsky ◽  
Theodore Laopoulos ◽  
Anatoly Sachenko ◽  
Lucio Grandinetti
Keyword(s):  
Step Rate ◽  
Rate Estimation

Examination of DIP Accident Rate Estimation Formula by Logistic Regression

2016 ◽  
Vol 2 (06) ◽  
pp. 374-378
Author(s):  
Takaharu Kunizane ◽  
Akira Koizumi ◽  
Toyono Inakazu ◽  
Yasuhiro Arai ◽  
Tetsuji Shitabo ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Accident Rate ◽  
Rate Estimation ◽  
Estimation Formula

Satellite Spin Rate Estimation Method by Measuring the Received Power Data at Two Points

2017 ◽  
Vol 137 (3) ◽  
pp. 547-548
Author(s):  
Ryuichi Mitsuhashi ◽  
Ryosuke Hayasaka ◽  
Shin Satori ◽  
Masami Sasaki
Keyword(s):  
Estimation Method ◽  
Rate Estimation ◽  
Received Power ◽  
Satellite Spin

Technique for Improving the Flow Rate Estimation Range by Using an Axial Flow Water Turbine Generator

2017 ◽  
Vol 137 (1) ◽  
pp. 30-35
Author(s):  
Hiroaki Narita ◽  
Makoto Saruwatari ◽  
Jun Matsui ◽  
Yasutaka Fujimoto
Keyword(s):  
Flow Rate ◽  
Axial Flow ◽  
Turbine Generator ◽  
Rate Estimation ◽  
Water Turbine ◽  
Estimation Range

IS STEP RATE ASSOCIATED WITH RUNNING INJURY INCIDENCE? AN OBSERVATIONAL STUDY WITH 9- MONTH FOLLOW UP

2020 ◽  
Vol 15 (2) ◽  
pp. 221-228
Author(s):  
Eliza B. Szymanek ◽  
Erin M. Miller ◽  
Amy N. Weart ◽  
Jamie B. Morris ◽  
Donald L. Goss
Keyword(s):  
Observational Study ◽  
Injury Incidence ◽  
Step Rate ◽  
Running Injury

Double-smoothing in Kernel Hazard Rate Estimation

2008 ◽  
Vol 47 (02) ◽  
pp. 167-173 ◽  
Author(s):  
A. Pfahlberg ◽  
O. Gefeller ◽  
R. Weißbach
Keyword(s):  
Hazard Rate ◽  
Nearest Neighbor ◽  
Bandwidth Selection ◽  
Study Data ◽  
Computational Effort ◽  
Finite Sample ◽  
Adaptive Smoothing ◽  
Rate Estimation ◽  
Data Adaptive ◽  
Double Smoothing

Summary Objectives: In oncological studies, the hazard rate can be used to differentiate subgroups of the study population according to their patterns of survival risk over time. Nonparametric curve estimation has been suggested as an exploratory means of revealing such patterns. The decision about the type of smoothing parameter is critical for performance in practice. In this paper, we study data-adaptive smoothing. Methods: A decade ago, the nearest-neighbor bandwidth was introduced for censored data in survival analysis. It is specified by one parameter, namely the number of nearest neighbors. Bandwidth selection in this setting has rarely been investigated, although the heuristical advantages over the frequently-studied fixed bandwidth are quite obvious. The asymptotical relationship between the fixed and the nearest-neighbor bandwidth can be used to generate novel approaches. Results: We develop a new selection algorithm termed double-smoothing for the nearest-neighbor bandwidth in hazard rate estimation. Our approach uses a finite sample approximation of the asymptotical relationship between the fixed and nearest-neighbor bandwidth. By so doing, we identify the nearest-neighbor bandwidth as an additional smoothing step and achieve further data-adaption after fixed bandwidth smoothing. We illustrate the application of the new algorithm in a clinical study and compare the outcome to the traditional fixed bandwidth result, thus demonstrating the practical performance of the technique. Conclusion: The double-smoothing approach enlarges the methodological repertoire for selecting smoothing parameters in nonparametric hazard rate estimation. The slight increase in computational effort is rewarded with a substantial amount of estimation stability, thus demonstrating the benefit of the technique for biostatistical applications.

A FrFT Based Algorithm for Doppler Frequency Rate Estimation from LFM Coherent Pulse Train

2010 ◽  
Vol 32 (11) ◽  
pp. 2718-2723 ◽  
Author(s):  
Hong Li ◽  
Yu-liang Qin ◽  
Yan-peng Li ◽  
Hong-qiang Wang ◽  
Xiang Li
Keyword(s):  
Pulse Train ◽  
Doppler Frequency ◽  
Rate Estimation ◽  
Frequency Rate ◽  
Coherent Pulse
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