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Intelligent Recognition for Traditional Chinese Medicine (TCM) Pulse Signals

Author: WangRuXu
Tutor: YangLing
School: Lanzhou University
Course: Communication and Information System
Keywords: Identifying Pulse Time-frequency domain analysis Chaotic Characteristic Analysis Neural Networks Complex networks
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 67
Quote: 0
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Abstract


Reaction due to the change of the TCM Pulse Rise and Fall of the blood of human organs, the doctor of Chinese medicine through the touch-pressure sensation organs (such as fingers) human body pulse information, and thus achieve the purpose of the medical consultation. Although the medical consultation process is simple, non-invasive, but is mainly built on the basis of individual clinical experience of the doctor. In addition, due to the difference in sensitivity of the sense organs and subjective factors, largely limits the development and exchange of pulse diagnosis objective. Therefore, the study of pulse diagnosis objectifying identification of innovative methods, will play a great role in promoting the research of pulse diagnosis. According to the modern control theory and system point of view of the information processing by the output signal of the analysis system can know the internal state of the system. Therefore, the human body is a complex system output pulse signal as the object of study, combined with the pulse of modern signal processing methods and our traditional school, will become an effective way to move toward an objective and scientific road TCM Pulse Research. In this paper, the pulse formation mechanism and pulse diagnosis theory, first of all, start from cognitive pulse signal through frequency domain analysis methods, extracting time-frequency domain features used to differentiate between pulse; through chaotic characteristic analysis method, qualitative and quantitative analysis of pulse Chaotic Characteristics, correlation dimension, largest Lyapunov exponent the Kolmogorov entropy three magnitude as chaotic characteristic parameters to distinguish between different pulse. Secondly, according to the characteristics of the pulse, it is designed for identification TCM pulse neural network recognition. The identification device is designed for the echo state network (Echo State Network, ESN) deficiencies in the identification of multiple information characterized. Adaptive technology and clustering algorithm based on complex network theory and Lyapunov stability theorem, complex network adaptive clustering synchronization controller is designed to give sufficient conditions for cluster synchronization to achieve global stability. After this controller as an intermediate layer, the design of a novel adaptive clustering sync echo state network identification model. Theoretical and numerical analysis proved the robustness of the recognizer model input, feedback, and other variables, in the recognition process, simply adjust the state matrix can be achieved global stability; same time, the network can effectively mimic the human brain to identify diverse the information characteristic time sequence process, with the characteristics of adaptive clustering. Finally, in recognition of pulse signals to test the validity of the model of the recognizer, and comparison with the traditional neural network identifier further validate its superiority.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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