Principle Component Analysis

Author(s):  
David Zhang ◽  
Xiao-Yuan Jing ◽  
Jian Yang

In this chapter, we first describe some basic concepts of PCA, a useful statistical technique that can be used in many fields, such as face patterns and other biometrics. Then, we introduce PCA definitions and related technologies. Following, we discuss non-linear PCA technologies. Finally, some useful conclusions are summarized.

Author(s):  
Yuli Naulita

The water masses in both routes of Indonesia Throughflow (ITF) from historical hydrographic data are examined by means of the Principal Component Analysis (PCA), a multivariate statistical technique, during the southeast monsoon and northwest monsoon, and compared with the TS diagrams. The temperature and dissolves oxygen always play in the same PC, which describeds a variability contribution of the water mass characters, while salinity in a different PC. The relationship of the water masses parameters may indicate the character of dissolved oxygen as a non-conservation tracer. The Principle Component Analysis may also be used to follow the trendds of core layer attenuation as verified by the salinity corresponds at the PC. It will be higher with S-max and S-min and more closely resemble the sources. This condition is shown in the waters close to the main sources in the Pacific, like Sulawesi, Malkuku and Halmahera Sea, where both the salinity extrema can still be observed. Conversely, in the Banda and Timor Sea, where S-max and S-min are greatly attenuated even completely remove, the correspondence of salinity in the water mass character variability becomes smaller. As seen on TS and TO diagrams, PCA graphics are also showed the dominant of the north Pacific water in the western route seas, the Sulawesi, Makasar Strait and the Florest Sea, but relatively salty water of South Pacific origin is observed in the Halmahera Sea, particularly in the northwest monsoon. The strong seasonal variablity of surface water in the Indonesian can also be observed in the PCA graphics. Keywords: Water Mass, Indonesian Throughflow, PCA.


Author(s):  
Basavaraj N Hiremath ◽  
Malini M Patilb

The voice recognition system is about cognizing the signals, by feature extraction and identification of related parameters. The whole process is referred to as voice analytics. The paper aims at analysing and synthesizing the phonetics of voice using a computer program called “PRAAT”. The work carried out in the paper also supports the analysis of voice segmentation labelling, analyse the unique features of voice cues, understanding physics of voice, further the process is carried out to recognize sarcasm. Different unique features identified in the work are, intensity, pitch, formants related to read, speak, interactive and declarative sentences by using principle component analysis.


2003 ◽  
Vol 26 (6) ◽  
pp. 681-682
Author(s):  
Harry Howard

Jackendoff's criticisms of the current state of theorization in cognitive neuroscience are defused by recent work on the computational complementarity of the hippocampus and neocortex. Such considerations lead to a grounding of Jackendoff's processing model in the complementary methods of pattern analysis effected by independent component analysis (ICA) and principle component analysis (PCA).


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