Microphonic noise cancellation in radiation detectors using real-time adaptive modeling

2014 ◽  
Author(s):  
Victoria Moeller-Chan ◽  
Thomas Hasenohr ◽  
Thorsten Stezelberger ◽  
Marcos Turqueti ◽  
Sergio Zimmermann
Keyword(s):  
Real Time ◽  
Radiation Detectors ◽  
Noise Cancellation ◽  
Adaptive Modeling

scholarly journals Development and Evaluation of Light-Weight Active Noise Cancellation Earphones

2018 ◽  
Vol 8 (7) ◽  
pp. 1178 ◽  
Author(s):  
Sen Kuo ◽  
Yi-Rou Chen ◽  
Cheng-Yuan Chang ◽  
Chien-Wen Lai
Keyword(s):  
Noise Reduction ◽  
Real Time ◽  
Random Noise ◽  
Active Noise Control ◽  
Noise Cancellation ◽  
Experimental Results ◽  
Path Model ◽  
Light Weight ◽  
Active Noise ◽  
Natural Sound

This paper presents the development of active noise control (ANC) for light-weight earphones, and proposes using music or natural sound to estimate the critical secondary path model instead of extra random noise. Three types of light-weight ANC earphones including in-ear, earbud, and clip phones are developed. Real-time experiments are conducted to evaluate their performance using the built-in microphone inside KEMAR’s ear and to compare with commercially-available ANC headphones and earphones. Experimental results show that the developed light-weight ANC earphones achieve higher noise reduction than the commercial ANC headphones and earphones, and the in-ear ANC earphone has the best noise reduction performance.

Adaptive Modeling and Dynamic Targeting for Real Time Analytics in Mobile Advertising

2017 ◽  
Vol 7 (2) ◽  
pp. 24-39 ◽  
Author(s):  
Donald Kridel ◽  
Dan Dolk ◽  
David Castillo
Keyword(s):  
Real Time ◽  
Predictive Analytics ◽  
User Behavior ◽  
Model Management ◽  
Mobile Marketing ◽  
Time Data ◽  
Adaptive Modeling ◽  
Very Large Databases ◽  
Customer Profiling ◽  
Modeling Strategy

Mobile marketing campaigns are now largely deployed through demand side platforms (DSPs) who provide dynamic customer targeting and a performance-intensive real-time bidding (RTB) version of predictive analytics as a service. Matching users with the campaigns they are most likely to engage with in extreme real-time environments requires adaptive model management, advanced parallel processing hardware/software, and the integration of multiple very large databases. The authors present (1) an adaptive modeling strategy to satisfy the performance thresholds of 40 to 100ms for DSPs to decide whether and how much to bid for a potential client to receive a particular advertisement via their mobile device. (2) a dynamic customer profiling technique to map mobile devices to specific lattices (geographic locations), and to track user behavior via device-histories. In this “big data” decision environment, analytic model management is automated via model feedback loops which adjust the models dynamically as real-time data streams in.

Active Noise Control Based on TMS320C5509

2013 ◽  
Vol 631-632 ◽  
pp. 1172-1176
Author(s):  
Yong Wei Ma ◽  
Xin Ke Gou ◽  
Xian Jun Du ◽  
Chong Yu Ren
Keyword(s):  
Control System ◽  
Real Time ◽  
Noise Control ◽  
Active Noise Control ◽  
Noise Cancellation ◽  
Real Time Control ◽  
Time Control ◽  
Active Noise ◽  
Fxlms Algorithm ◽  
Mixed Language

The feed-forward adaptive active noise control (AANC) system is presented. Firstly, the hardware project of the system is brought forward, by selecting TMS320C5509 DSP as the controller. Then, using the mixed language, the active noise real-time control system is realized, based on the FXLMS algorithm. It’s proved that a good noise cancellation is achieved by the experiment.

Real-time vehicle noise cancellation techniques for gunshot acoustics

2012 ◽  
Author(s):  
Antonio L. L. Ramos ◽  
Sverre Holm ◽  
Sigmund Gudvangen ◽  
Ragnvald Otterlei
Keyword(s):  
Real Time ◽  
Noise Cancellation ◽  
Vehicle Noise
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