25,322 research outputs found

    Active Noise Control with Sampled-Data Filtered-x Adaptive Algorithm

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    Analysis and design of filtered-x adaptive algorithms are conventionally done by assuming that the transfer function in the secondary path is a discrete-time system. However, in real systems such as active noise control, the secondary path is a continuous-time system. Therefore, such a system should be analyzed and designed as a hybrid system including discrete- and continuous- time systems and AD/DA devices. In this article, we propose a hybrid design taking account of continuous-time behavior of the secondary path via lifting (continuous-time polyphase decomposition) technique in sampled-data control theory

    Design of a digital compression technique for shuttle television

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    The determination of the performance and hardware complexity of data compression algorithms applicable to color television signals, were studied to assess the feasibility of digital compression techniques for shuttle communications applications. For return link communications, it is shown that a nonadaptive two dimensional DPCM technique compresses the bandwidth of field-sequential color TV to about 13 MBPS and requires less than 60 watts of secondary power. For forward link communications, a facsimile coding technique is recommended which provides high resolution slow scan television on a 144 KBPS channel. The onboard decoder requires about 19 watts of secondary power

    A Novel Adaptive Spectrum Noise Cancellation Approach for Enhancing Heartbeat Rate Monitoring in a Wearable Device

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    This paper presents a novel approach, Adaptive Spectrum Noise Cancellation (ASNC), for motion artifacts removal in Photoplethysmography (PPG) signals measured by an optical biosensor to obtain clean PPG waveforms for heartbeat rate calculation. One challenge faced by this optical sensing method is the inevitable noise induced by movement when the user is in motion, especially when the motion frequency is very close to the target heartbeat rate. The proposed ASNC utilizes the onboard accelerometer and gyroscope sensors to detect and remove the artifacts adaptively, thus obtaining accurate heartbeat rate measurement while in motion. The ASNC algorithm makes use of a commonly accepted spectrum analysis approaches in medical digital signal processing, discrete cosine transform, to carry out frequency domain analysis. Results obtained by the proposed ASNC have been compared to the classic algorithms, the adaptive threshold peak detection and adaptive noise cancellation. The mean (standard deviation) absolute error and mean relative error of heartbeat rate calculated by ASNC is 0.33 (0.57) beats¡min-1 and 0.65%, by adaptive threshold peak detection algorithm is 2.29 (2.21) beats¡min-1 and 8.38%, by adaptive noise cancellation algorithm is 1.70 (1.50) beats¡min-1 and 2.02%. While all algorithms performed well with both simulated PPG data and clean PPG data collected from our Verity device in situations free of motion artifacts, ASNC provided better accuracy when motion artifacts increase, especially when motion frequency is very close to the heartbeat rate

    A turn-key Concept for active cancellation of Global Positioning System L3 Signal

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    We present a concept, developed at the National Astronomy and Ionosphere Center (NAIC) at Arecibo, Puerto Rico, for active suppression of Global Positioning System (GPS) signals in the 305 m dish radio receiver path prior to backend processing. The subsystem does not require an auxiliary antenna and is intended for easy integration with radio telescope systems with a goal of being a turnkey addition to virtually any facility. Working with actual sampled signal data, we have focused on the detection and cancellation of the GPS L3 signal at 1381.05 MHz which, during periodic test modes and particularly during system-wide tests, interfere with observations of objects in a range of redshifts that includes the Coma supercluster, for example. This signal can dynamically change modulation modes and our scheme is capable of detecting these changes and applying cancellation or sending a blanking signal, as appropriate. The subsystem can also be adapted to GPS L1 (1575.42 MHz), L2C (1227.6 MHz), and others. A follow-up is underway to develop a prototype to deploy and evaluate at NAIC.Comment: Presented at the RFI mitigation workshop, 29-31 March 2010, Groningen, the Netherlands. Accepted for publication by the Proceedings of Scienc

    Acitve noise control in three dimension enclosure using piezoceramics

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    Analysis and experiment are undertaken to attenuate the three dimension enclosure noise using piezoceramics. A flexible aluminium plate and five wood walls are constructed with clamped four edges conditions. Noise is generated by speaker and transmitted to the three dimension enclosure. Piezoceramics are used to control the noise inside. A microphone is put inside to monitor the noise. State space method is used to identify the system, the vibration mode and acoustic mode is also researched. Different arithmetic is used to control the noise inside. The sound pressure level reduction at selected point is observed

    A constrained, total-variation minimization algorithm for low-intensity X-ray CT

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    Purpose: We develop an iterative image-reconstruction algorithm for application to low-intensity computed tomography (CT) projection data, which is based on constrained, total-variation (TV) minimization. The algorithm design focuses on recovering structure on length scales comparable to a detector-bin width. Method: Recovering the resolution on the scale of a detector bin, requires that pixel size be much smaller than the bin width. The resulting image array contains many more pixels than data, and this undersampling is overcome with a combination of Fourier upsampling of each projection and the use of constrained, TV-minimization, as suggested by compressive sensing. The presented pseudo-code for solving constrained, TV-minimization is designed to yield an accurate solution to this optimization problem within 100 iterations. Results: The proposed image-reconstruction algorithm is applied to a low-intensity scan of a rabbit with a thin wire, to test resolution. The proposed algorithm is compared with filtered back-projection (FBP). Conclusion: The algorithm may have some advantage over FBP in that the resulting noise-level is lowered at equivalent contrast levels of the wire.Comment: This article has been submitted to "Medical Physics" on 9/13/201

    Performance characterization of clustering algorithms for colour image segmentation

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    This paper details the implementation of three traditional clustering techniques (K-Means clustering, Fuzzy C-Means clustering and Adaptive K-Means clustering) that are applied to extract the colour information that is used in the image segmentation process. The aim of this paper is to evaluate the performance of the analysed colour clustering techniques for the extraction of optimal features from colour spaces and investigate which method returns the most consistent results when applied on a large suite of mosaic images
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