A pitch detection method based on harmonic-tone theory and variable sampling rate technique

2015 ◽  
pp. 427-430
Author(s):  
Z Pan ◽  
Y Feng
Keyword(s):  
Detection Method ◽  
Sampling Rate ◽  
Pitch Detection ◽  
Variable Sampling

Economic design of a variable sampling rate EWMA chart

2004 ◽  
Vol 36 (5) ◽  
pp. 387-399 ◽  
Author(s):  
CHANGSOON PARK ◽  
JAEHEON LEE ◽  
YOUNGIL KIM
Keyword(s):  
Sampling Rate ◽  
Economic Design ◽  
Ewma Chart ◽  
Variable Sampling

scholarly journals An Improved Roadside Parking Space Occupancy Detection Method Based on Magnetic Sensors and Wireless Signal Strength

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2348 ◽  
Author(s):  
Liangliang Lou ◽  
Jinyi Zhang ◽  
Yong Xiong ◽  
Yanliang Jin
Keyword(s):  
Detection Method ◽  
Dead Zone ◽  
Sampling Rate ◽  
Vehicle Detection ◽  
Magnetic Sensors ◽  
Experimental Results ◽  
Detection Accuracy ◽  
Parking Space ◽  
Wireless Transceivers ◽  
Occupancy Detection

Smart Parking Management Systems (SPMSs) have become a research hotspot in recent years. Many researchers are focused on vehicle detection technology for SPMS which is based on magnetic sensors. Magnetism-based wireless vehicle detectors (WVDs) integrate low-power wireless communication technology, which improves the convenience of construction and maintenance. However, the magnetic signals are not only susceptible to the adjacent vehicles, but also affected by the magnetic signal dead zone of high-chassis vehicles, resulting in a decrease in vehicle detection accuracy. In order to improve the vehicle detection accuracy of the magnetism-based WVDs, the paper introduces an RF-based vehicle detection method based on the characteristics analysis of received signal strengths (RSSs) generated by the wireless transceivers. Since wireless transceivers consume more energy than magnetic sensors, the proposed RF-based method is only activated to extract the data characteristics of RSSs to further judge the states of vehicles when the data feature of magnetic signals is not sufficient to provide accurate judgment on parking space status. The proposed method was evaluated in an actual roadside parking lot and experimental results show that when the sampling rate of magnetic sensor is 1 Hz, the vehicle detection accuracy is up to 99.62%. Moreover, compared with machine-learning-based vehicle detection method, the experimental results show that our method has achieved a good compromise between detection accuracy and power consumption.

Adaptive high-gain λ-tracking with variable sampling rate

1999 ◽  
Vol 36 (4) ◽  
pp. 285-293 ◽  
Author(s):  
Achim Ilchmann ◽  
Stuart Townley
Keyword(s):  
Sampling Rate ◽  
High Gain ◽  
Variable Sampling
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