Feature Dimension Reduction of Multisensor Data Fusion using Principal Component Fuzzy Analysis

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Kashanian H.; Dabaghi E.

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Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF ENGINEERING Year:2017 | Volume:30 | Issue:4 (TRANSACTIONS A: Basics) Page(s): 493-499

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Title

Feature Dimension Reduction of Multisensor Data Fusion using Principal Component Fuzzy Analysis

Author(s)

Kashanian H. | Dabaghi E. | Issue Writer Certificate

Keywords

Principle Components Fuzzy Analysis

Multisensor Data Fusion

Ubiquitous Activities Monitoring

Intelligent Devices

Health Care

Abstract

These days, the most important areas of research in many different applications, with different tools, are focused on how to get awareness. One of the serious applications is the awareness of the behavior and activities of patients. The importance is due to the need of ubiquitous medical care for individuals. That the doctor knows the patient's physical condition, sometimes is very important. Of course, there are other important applications for this information. There are a variety of methods and tools for measurement, gathering, and analysis of the physical behaviors and activities’ information. One of the most successful tools for this aim are ubiquitous intelligent electronic devices, specifically smartphones, and smart watches. There are many sensors in these devices, some of which can be used to understand the activities of daily living. As an output result, these sensors produce many raw data. Thus, it is needed to process these information and recognize the individual behavior of the output of this processing. In this paper, the basic components of the analysis phase for this process have been proposed. Simulations validate the benefits and superiority of this method.

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APA: Copy

Kashanian, H., & Dabaghi, E.. (2017). Feature Dimension Reduction of Multisensor Data Fusion using Principal Component Fuzzy Analysis. INTERNATIONAL JOURNAL OF ENGINEERING, 30(4 (TRANSACTIONS A: Basics)), 493-499. SID. https://sid.ir/paper/724279/en

Vancouver: Copy

Kashanian H., Dabaghi E.. Feature Dimension Reduction of Multisensor Data Fusion using Principal Component Fuzzy Analysis. INTERNATIONAL JOURNAL OF ENGINEERING[Internet]. 2017;30(4 (TRANSACTIONS A: Basics)):493-499. Available from: https://sid.ir/paper/724279/en

IEEE: Copy

H. Kashanian, and E. Dabaghi, “Feature Dimension Reduction of Multisensor Data Fusion using Principal Component Fuzzy Analysis,” INTERNATIONAL JOURNAL OF ENGINEERING, vol. 30, no. 4 (TRANSACTIONS A: Basics), pp. 493–499, 2017, [Online]. Available: https://sid.ir/paper/724279/en

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