Circular-harmonic function, minimum average correlation energy filters

1991 ◽  
Vol 30 (35) ◽  
pp. 5169 ◽  
Author(s):  
David Casasent ◽  
Anand Iyer ◽  
Gopalan Ravichandran
Keyword(s):  
Harmonic Function ◽  
Correlation Energy ◽  
Average Correlation

Target Recognition Technology Based on Minimum Average Correlation Energy Filters

2010 ◽  
Vol 47 (6) ◽  
pp. 061002
Author(s):  
贾欢欢 Jia Huanhuan ◽  
杨璐 Yang Lu ◽  
王文生 Wang Wensheng
Keyword(s):  
Correlation Energy ◽  
Target Recognition ◽  
Average Correlation

scholarly journals Anomaly Detection in Electroencephalogram Signals Using Unconstrained Minimum Average Correlation Energy Filter

2009 ◽  
Vol 5 (7) ◽  
pp. 501-506 ◽  
Author(s):  
Aini Hussain ◽  
Rosniwati Ghafar ◽  
Salina Abdul Samad ◽  
Nooritawati Md Tahir
Keyword(s):  
Anomaly Detection ◽  
Correlation Energy ◽  
Average Correlation ◽  
Unconstrained Minimum

scholarly journals Genre Classification of Traditional Malay Music Using Spectrogram Correlation

2018 ◽  
Vol 7 (4.11) ◽  
pp. 29
Author(s):  
S. A. Samad ◽  
A. B. Huddin
Keyword(s):  
Template Matching ◽  
Correlation Energy ◽  
Recognition Rate ◽  
Salient Feature ◽  
Average Correlation ◽  
Genre Classification ◽  
Average Recognition Rate ◽  
Number Of Segments ◽  
Unconstrained Minimum

A method to classify the genre of traditional Malay music using spectrogram correlation is described.  The method can be divided into three distinct parts consisting of spectrogram construction that retains the most salient feature of the music, template construction that takes into account the variations in music within a genre as well as the music progresses, and template matching based on spectrogram image cross-correlation with unconstrained minimum average correlation energy filters. Experiments conducted with seven genres of traditional Malay music show that the recognition accuracy is dependent on the number of segments used to construct the filter templates, which in turn is related to the length of music segment used. Despite using a small dataset, an average recognition rate of 61.8 percent was obtained for music segments lasting 180 seconds using six relatively short excerpts.  

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