Headphones with an integrated active noise cancellation system have been increasingly introduced to the consumer market in recent years. When exposing the human ear to active noise sources in this striking distance, t...Headphones with an integrated active noise cancellation system have been increasingly introduced to the consumer market in recent years. When exposing the human ear to active noise sources in this striking distance, the ensuring of a safe sound pressure level is vital. In feedback systems, this is coupled with the stability of the closed control loop; stable controller design is thus essential. However, changes in the control path during run-time can cause the stable control system to become unstable, resulting in an overdrive of the speakers in the headphones. This paper proposes a method, which enables the real-time analysis of the current system state and if necessary stabilizes the closed loop while maintaining the active noise reduction. This is achieved by estimating and evaluating the open loop behavior with an adaptive filter and subsequently limiting the controller gain in respect to the stability margin.展开更多
In recent years,context aware technology has been widely used in many fields,such as internet of vehicles(IoV).Consistent context information plays a vital role in adapting a system to rapidly changing situations.Howe...In recent years,context aware technology has been widely used in many fields,such as internet of vehicles(IoV).Consistent context information plays a vital role in adapting a system to rapidly changing situations.However,sensor's precision variance,equipment heterogeneity,network delay and the difference of statistical algorithms can lead to inconsistency context and inappropriate services.In this paper,we present an effective algorithm of context inconsistent elimination which is based on feedback and adjusted basic reliability distribution.Through feedback,each sensor's perception precision can be obtained,and with the adjusted basic reliability distribution scheme,we can make full use of all context information by adjusting the influence of every context on whole judgment based on sensor's perception precision and threshold of sensor's perception precision,and then eliminate context inconsistency.In order to evaluate the performance of the proposed context inconsistency elimination algorithm,context aware rate is defined.The simulation results show that the proposed context inconsistency elimination algorithm can obtain the best context aware rate in most cases for the varied error rates of sensors.展开更多
文摘Headphones with an integrated active noise cancellation system have been increasingly introduced to the consumer market in recent years. When exposing the human ear to active noise sources in this striking distance, the ensuring of a safe sound pressure level is vital. In feedback systems, this is coupled with the stability of the closed control loop; stable controller design is thus essential. However, changes in the control path during run-time can cause the stable control system to become unstable, resulting in an overdrive of the speakers in the headphones. This paper proposes a method, which enables the real-time analysis of the current system state and if necessary stabilizes the closed loop while maintaining the active noise reduction. This is achieved by estimating and evaluating the open loop behavior with an adaptive filter and subsequently limiting the controller gain in respect to the stability margin.
基金supported by Scientific Research Foundation for the Excellent Young and Middle-aged Scientists of Shandong Province(No.BS2012DX024)Independent Innovation Foundation of Shandong University(No.2012ZD035)Technical Innovative Project of Shandong Province(No.201230201031,No.201320201024)
文摘In recent years,context aware technology has been widely used in many fields,such as internet of vehicles(IoV).Consistent context information plays a vital role in adapting a system to rapidly changing situations.However,sensor's precision variance,equipment heterogeneity,network delay and the difference of statistical algorithms can lead to inconsistency context and inappropriate services.In this paper,we present an effective algorithm of context inconsistent elimination which is based on feedback and adjusted basic reliability distribution.Through feedback,each sensor's perception precision can be obtained,and with the adjusted basic reliability distribution scheme,we can make full use of all context information by adjusting the influence of every context on whole judgment based on sensor's perception precision and threshold of sensor's perception precision,and then eliminate context inconsistency.In order to evaluate the performance of the proposed context inconsistency elimination algorithm,context aware rate is defined.The simulation results show that the proposed context inconsistency elimination algorithm can obtain the best context aware rate in most cases for the varied error rates of sensors.
