scholarly journals Identifying group contributions in NBA lineups with spectral analysis

2020 ◽  
Vol 6 (3) ◽  
pp. 215-234
Author(s):  
Stephen Devlin ◽  
David Uminsky
Keyword(s):  
Signal Processing ◽  
Spectral Analysis ◽  
Lower Order ◽  
Group Contributions ◽  
Team Success ◽  
Practical Tool

We address the question of how to quantify the contributions of groups of players to team success. Our approach is based on spectral analysis, a technique from algebraic signal processing, which has several appealing features. First, our analysis decomposes the team success signal into components that are naturally understood as the contributions of player groups of a given size: individuals, pairs, triples, fours, and full five-player lineups. Secondly, the decomposition is orthogonal so that contributions of a player group can be thought of as pure: Contributions attributed to a group of three, for example, have been separated from the lower-order contributions of constituent pairs and individuals. We present detailed a spectral analysis using NBA play-by-play data and show how this can be a practical tool in understanding lineup composition and utilization.

Experimental Investigation on the Use of Bispectral Analysis in Detecting Nonlinear Faults in Hydraulic Machines

2014 ◽  
Vol 606 ◽  
pp. 147-151 ◽  
Author(s):  
M.S. Somia Alfatih ◽  
M. Salman Leong ◽  
L.M. Hee
Keyword(s):  
Experimental Study ◽  
Experimental Investigation ◽  
Signal Processing ◽  
Spectral Analysis ◽  
Centrifugal Pump ◽  
Nonlinear Behavior ◽  
Suction Side ◽  
Bispectral Analysis ◽  
Detection And Identification ◽  
Hydraulic Machines

Bispectral analysis is one of the relatively more recent tools in signal processing used for detection and identification of higher harmonics in a signal. It is also acknowledged to be one of Higher Order Spectral Analysis (HOSA) effective tools for detecting nonlinear behavior in mechanical systems. In this study, vibration sources in a hydraulic machine which may have features of nonlinear behavior were investigated. An experimental study was undertaken to formulate a more sensitive and effective method using Bispectral analysis to diagnose cavitation in a centrifugal pump facility. Cavitation was induced on the suction side of the pump. The cavitation signal was analyzed with and without induced cavitation conditions at different locations on the pump, and analyzed using FFT and bispectrum methods. It was observed that bispectral analysis could be used as an early indicator of cavitation with changes for severity of cavitation.

Higher-order spectral analysis in laser-Doppler flowmetry signal processing

1999 ◽  
Vol 7 (2-3) ◽  
pp. 85-101 ◽  
Author(s):  
Vassilios Alexopoulos ◽  
Stefanos Kollias ◽  
Philippe Leger ◽  
Henry Boccalon ◽  
Zoltan Csiki
Keyword(s):  
Signal Processing ◽  
Spectral Analysis ◽  
Laser Doppler Flowmetry ◽  
Higher Order ◽  
Laser Doppler ◽  
Doppler Flowmetry

Resolving the Issues of Capon and APES Approach for Projecting Enhanced Spectral Estimation

2016 ◽  
Vol 6 (2) ◽  
pp. 725
Author(s):  
Kantipudi MVV Prasad ◽  
H.N. Suresh
Keyword(s):  
Signal Processing ◽  
Spectral Analysis ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Simple Technique ◽  
Spectral Estimation ◽  
Research Work ◽  
Research Community ◽  
The Past ◽  
Power Spectral

There are various applications on signal processing that is highly dependent on preciseness and accuracy of the outcomes in spectrum of signals. Hence, from the past two decades the research community has recognized the benefits, significance, as well as associated problems in carrying out a model for spectral estimation. While in-depth investigation of the existing literatures shows that there are various attempts by the researchers to solve the issues associated with spectral estimations, where majority of teh research work is inclined towards addressing problems associated with Capon and APES techniques of spectral analysis. Therefore, this paper introduces a very simple technique towards resolving the issues of Capon and APES techniques. The outcome of the study was analyzed using correlational factor and power spectral density to find the proposed system offers better spectral estimations compared to existing system.

A Hybrid Signal Processing Approach to Sensor Data Analysis

2003 ◽  
Author(s):  
Ruqiang Yan ◽  
Robert X. Gao
Keyword(s):  
Signal Processing ◽  
Spectral Analysis ◽  
Energy Content ◽  
Sensor Data ◽  
Wavelet Coefficients ◽  
Mother Wavelet ◽  
New Approach ◽  
Analysis Techniques ◽  
Processing Approach ◽  
Envelope Spectrum

This paper presents a hybrid signal processing approach combining the wavelet transform and spectral analysis. A new approach to selecting a mother wavelet for decomposition of vibration signals was demonstrated. Subsequently, the bestsuited decomposition scale was selected based on the energy content of the wavelet coefficients. Subsequently, the envelope spectrum of the wavelet coefficients at the best-suited decomposition scale was used to identify the defect and its location. Experimental analysis of signals from a defect-seeded bearing has shown that the developed approach is more efficient than the conventional spectral analysis techniques.

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