Spectral analysis and performance of a 20 kW CW uplink transmitter

2002 ◽  
Author(s):  
A. Silva
Keyword(s):  
Spectral Analysis ◽  
And Performance

scholarly journals Machine Learning for Waveform Spectral Analysis on Nuclear Explosion Signal and Performance of Broadband Vertical Component

2018 ◽  
Vol 1120 ◽  
pp. 012083 ◽  
Author(s):  
Kerista Tarigan ◽  
Marzuki Sinambela ◽  
Melda Panjaitan ◽  
Pandi Simangunsong ◽  
Henry Kristian Siburian
Keyword(s):  
Machine Learning ◽  
Spectral Analysis ◽  
Nuclear Explosion ◽  
Vertical Component ◽  
And Performance

Cycle and performance of mutual funds – an application of spectral analysis

2010 ◽  
Vol 18 (1) ◽  
pp. 75-79 ◽  
Author(s):  
Pao-Peng Hsu ◽  
Chen-Hui Yen ◽  
Ya-Hui Chang ◽  
Li-Ling Chou
Keyword(s):  
Spectral Analysis ◽  
Mutual Funds ◽  
And Performance

A Fast Rational Model Approach to Parametric Spectral Estimation—Part II: Properties and Performance Evaluation

1990 ◽  
Vol 112 (3) ◽  
pp. 328-336 ◽  
Author(s):  
S. D. Fassois
Keyword(s):  
Spectral Analysis ◽  
Performance Evaluation ◽  
Spectral Estimation ◽  
Rational Model ◽  
Basic Form ◽  
Guaranteed Stability ◽  
Consistency Property ◽  
Alternative Techniques ◽  
And Performance ◽  
Model Approach

In the first part of this paper (Fassois, 1990), the basic form of a novel, fast rational model approach to parametric spectral estimation was introduced. In this second part the consistency property of the approach is proven, and two modified versions, characterized by mathematically guaranteed stability, developed. Unlike most alternative techniques, the proposed approach is then capable of effectively estimating all types of spectra, including those characterized by sharp valleys. Its performance is finally evaluated via numerical simulations and comparisons with the Blackman-Tukey and the AR spectral analysis methods.

Speech Analysis Systems

1992 ◽  
Vol 35 (2) ◽  
pp. 314-332 ◽  
Author(s):  
Charles Read ◽  
Eugene H. Buder ◽  
Raymond D. Kent
Keyword(s):  
Spectral Analysis ◽  
User Interface ◽  
Fundamental Frequency ◽  
Frequency Analysis ◽  
Data Exchange ◽  
Speech Analysis ◽  
Signal Acquisition ◽  
Data Formats ◽  
System Components ◽  
And Performance

Performance characteristics are reviewed for seven systems marketed for acoustic speech analysis: CSpeech, CSRE, ILS-PC, Kay Elemetrics model 5500 Sona-Graph, MacSpeech Lab II, MSL, and Signalyze. The characteristics reviewed include system components, basic capabilities (signal acquisition, waveform operations, analysis, and other functions), documentation, user interface, data formats and journaling, speed and precision of spectral analysis, and speed and precision of fundamental frequency analysis. Basic capabilities are also tabulated for three recently introduced systems: the Sensimetrics SpeechStation, the Kay Elemetrics Computerized Speech Lab (CSL), and the LSI Speech Workstation. In addition to the capability and performance summaries, this article offers suggestions for continued development of speech analysis systems, particularly in data exchange, journaling, display features, spectral analysis, and fundamental frequency analysis.

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