Ultra-compact electric vehicles (EVs) have been becoming increasingly popular recently. These vehicles have advanced characteristics such as compactness, light body, and low environmental impact. However, it is seriou...
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Ultra-compact electric vehicles (EVs) have been becoming increasingly popular recently. These vehicles have advanced characteristics such as compactness, light body, and low environmental impact. However, it is serious problem with interior noise which are from outside such as road noise and wind noise. Therefore, we have been studying an active noise control (ANC) system for ultra-compact EV by using the giant magnetostrictive actuator. In this paper, we propose a control system using an adaptive filter by least mean square (lms) algorithm which is updating a filter coefficient continuously and brings the reduce noise. Furthermore, we studied fundamental considerations on simulation and noise reduction experiments for the development new ANC system using the giant magnetostrictive actuator. We performed noise reduction simulation using lms algorithm and conducted low frequency noise simulated road noise reduction experiment by wall surface vibration using the giant magnetostrictive actuator. From the result of the simulation, the sound power became to close 0 Pa in the noise control system limitlessly by giving an appropriate step size parameter. Furthermore, in the noise reduction experiment, the sound pressure level of 200 Hz was reduced to 5.8 dB by controlling the noise. Comparing the results with the simulation, it was possible to reduce the noise level at the position of the driver's ears.
Bioelectricity signal is in strong interfering environment. When it is abstracted, filter is an important hinge. Adaptive interference canceller which based on lms algorithm is excellent. It can adjust system paramete...
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Bioelectricity signal is in strong interfering environment. When it is abstracted, filter is an important hinge. Adaptive interference canceller which based on lms algorithm is excellent. It can adjust system parameter automatically. When signals are abstracted or disposed, it can play better performance. With this algorithm, this paper dispose ECG(Electrocardiograph)signal as an example in two aspect: canceling power line interference and canceling baseline shift. Both get well effect.
This paper presents new data selective adaptive filtering algorithms. The algorithms are derived under the concept of set-membership filtering (SMF) and also use the concept of data reusing. The algorithms include dat...
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This paper presents new data selective adaptive filtering algorithms. The algorithms are derived under the concept of set-membership filtering (SMF) and also use the concept of data reusing. The algorithms include data-dependent step-sizes that provide fast convergence. The results show considerable performance improvement using the new algorithms for correlated input signals compared with the recently proposed set-membership Nlms (SM-Nlms) algorithm.
The authors have previously proposed a fuzzy stack filter that is defined by a fuzzy Boolean function. We have also presented a specific design method (called the fuzzy Boolean function determination method) for the m...
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The authors have previously proposed a fuzzy stack filter that is defined by a fuzzy Boolean function. We have also presented a specific design method (called the fuzzy Boolean function determination method) for the most fundamental fuzzy stack filter, the FCWM (fuzzy center weighted median). By varying the fuzzy Boolean function, we can achieve both an arbitrary CWM filter and a weighted average value filter in which only the weights at arbitrary processing points are varied. Hence, in comparison with the CWM filter, our filter is better at eliminating Gaussian noise. In this paper, to improve the reconstruction accuracy of nonsteady state signals, such as the image signals, a data-dependent FCWM (DD-FCWM) is proposed anew. The data-dependent filter is an adaptive filter in which the filter parameters are varied in response to the nature of the data near the processing point (local information). In a DD-FCWM filter, the fuzzy Boolean function is varied by using local information. We demonstrate that the proposed DD-FCWM filter uses the local signal information to appropriately vary, not only the weights of the processing points, but also the filter mode (average value type or median type). Furthermore, by use of image processing examples, we demonstrate that highly accurate signal reconstruction can be attained. (C) 1998 Scripta Technica.
Active control of vibration-induced noise in light weight train cars is of great interest since low weight trains are more economic but also have higher internal noise levels. This paper describes an approach to isola...
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Active control of vibration-induced noise in light weight train cars is of great interest since low weight trains are more economic but also have higher internal noise levels. This paper describes an approach to isolate bogie vibrations in such a way that the noise inside the car is reduced. An active control system with four inertial mass actuators fitted to the bogie were used to control bogie vibrations and noise inside the car. The tests were performed on an experimental light weight bogie fitted to a test car, in both lab environment and in foil scale tests on track at full speed.
A new deterrninistic adaptive identification and equalization approach is investigated based on an internal model principle to take account of time-varying dynamics of the channel parameters. The proposed adaptive alg...
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A new deterrninistic adaptive identification and equalization approach is investigated based on an internal model principle to take account of time-varying dynamics of the channel parameters. The proposed adaptive algorithm incorporates an internal model for compensating the dynamics of the time-varying parameters of the FIR channel model. The stability of the adaptation can be assured by designing the parameter adjusting dynamics in the actaptive algorithm by the help of the small gain theorem and passivity theorem. Its effectiveness of the proposed algorithms is examined and compared to ordinary lms approaches in numerical simulation of adaptive identification and equalization of a fading channel with parameters changing with a first-order function of time.
The elevators constructed today are increasingly fast and have a high level of comfort. However, this increase in speed means a higher level of noise inside the cabin, and this noise is normally compensated by passive...
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The elevators constructed today are increasingly fast and have a high level of comfort. However, this increase in speed means a higher level of noise inside the cabin, and this noise is normally compensated by passive means, that is, by improving the cabin's insulation. Low frequency noise persists, however, and it should be dealt with by active means. This article describes the practical application of Active Noise Control to an elevator cabin, greatly reducing the level of noise in the whole area. The results obtained are an advance towards the integration of Active Noise Control in elevators, and its commercialisation.
An adaptive equalization algorithm suitable for CM7.1 channel is proposed to address the problem of channel multipath fading in 60 GHz pulse communication system. The steady-state and bit error rate performances of th...
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An adaptive equalization algorithm suitable for CM7.1 channel is proposed to address the problem of channel multipath fading in 60 GHz pulse communication system. The steady-state and bit error rate performances of the proposed algorithm are analyzed based on the traditional lms and RLS algorithms, combined with the CM7.1 IEEE802.15.3c channel model, and compared with the traditional algorithm. Simulation results show that the algorithm reduces the computational complexity and verifies the feasibility of the algorithm in the 60 GHz pulse communication system with the premise of ensuring system reliability. Technical reference is provided for the application of high-capacity fifth-generation, high-frequency hot new empty scene.
The use of TMS320C31 DSP and FX-lms control algorithm in Active Noise Control system leaves time for additional digital signal processing. This time may be used for implementation of on-line identification algorithm t...
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The use of TMS320C31 DSP and FX-lms control algorithm in Active Noise Control system leaves time for additional digital signal processing. This time may be used for implementation of on-line identification algorithm to improve system performance in case of strong plant nonstationarities. The performance of the ANC system with off-line and on-line models identification is compared. The real-world experiments results show that the ANC system with on-line models identification can adapt to strong system configuration changes.
Mandibular movement is complex and individual due to variations in the temporomandibular joint (TMJ). Consequently, patient-centered dentistry should incorporate patients' specific anatomy and condylar function in...
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Mandibular movement is complex and individual due to variations in the temporomandibular joint (TMJ). Consequently, patient-centered dentistry should incorporate patients' specific anatomy and condylar function in treatment planning. Real-time magnetic resonance imaging (rt-MRI) visualizes relevant structures and tracks mandibular movement. However, current assessments rely on qualitative observations or time-consuming manual tracking, lacking reliability. This study developed an automatic tracking algorithm for mandibular movement in rt-MRI using least mean square registration (lms) and compared it to manual tracking (MT) during mouth opening. Ten participants with skeletal class I underwent rt-MRI (10 frames/s). The same operator tracked the condylar pathway for the two methods, setting 2000 landmarks (2 landmarks x100 frames x10 participants) for MT and 210 landmarks (3 landmarks x7 frames x10 participants) for lms. Time required, superimposition error, and the distance between tracked condylar pathways were compared between methods. lms tracking was 76% faster and showed significantly better superimposition (0.0289 +/- 0.0058) than MT (0.059 +/- 0.0145) (p = 0.002). During one-third of the movement, the pathways tracked by both methods were more than 1 mm and 1 degrees apart. These findings highlight the benefits of automatic condylar movement tracking in rt-MRI, laying the groundwork for more objective and quantitative observation of TMJ function.
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