Monolithic magnetic Hall sensor using dynamic quadrature offset cancellation

1997 ◽  
Vol 32 (6) ◽  
pp. 829-836 ◽  
Author(s):  
A. Bilotti ◽  
G. Monreal ◽  
R. Vig
Keyword(s):  
Hall Sensor ◽  
Offset Cancellation

scholarly journals Offset Cancellation and Programmable Gain Design for Switched Capacitor Amplifier in Digital DC-DC Converter

2021 ◽  
Vol 714 (4) ◽  
pp. 042053
Author(s):  
Panpan Zhang ◽  
Peng Zhao ◽  
Xiaoping Chen ◽  
Yang Song ◽  
Zongjiang Zhang
Keyword(s):  
Switched Capacitor ◽  
Offset Cancellation ◽  
Programmable Gain

Study of a modified non-contact Hall sensor-based flow transducer using centrifugal and momentum force principle

2021 ◽  
Author(s):  
Sirshendu Saha ◽  
Saikat Kumar Bera ◽  
Saurabh Pal ◽  
Satish Chandra Bera
Keyword(s):  
Hall Sensor ◽  
Flow Transducer

scholarly journals Multilayer Learning Network for Modulation Classification Assisted with Frequency Offset Cancellation in Satellite to Ground Link

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Guan Qing Yang
Keyword(s):  
Carrier Frequency ◽  
Carrier Frequency Offset ◽  
Frequency Offset ◽  
Training Sequence ◽  
Classification Performance ◽  
Modulation Classification ◽  
Correct Classification ◽  
Offset Cancellation ◽  
Learning Network ◽  
Hidden Layer

A multilayer learning network assisted with frequency offset cancellation is proposed for modulation classification in satellite to ground link. Carrier frequency offset greatly reduces modulation classification performance. It is necessary to cancel frequency offset before modulation classification. Frequency offset cancellation weights are established through multilayer learning network based on MSE criterion. Then the weight and hidden layer of multilayer learning network are also established for modulation classification. The hidden layers and weight are trained and tuned to combat the interference introduced by frequency offset. Compared with current modulation classification algorithm, the proposed multilayer learning network greatly improves the Probability of Correct Classification (PCC). It has been proven that the proposed multilayer learning network assisted with frequency offset has higher performance for modulation classification within the same training sequence.

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