Normally, Data acquisition (DAQ) is used to acquire the signals from different devices like sensors, transducers, actuators etc. The data acquisition is also used to analyze the signals, digitizing the signals and acq...Normally, Data acquisition (DAQ) is used to acquire the signals from different devices like sensors, transducers, actuators etc. The data acquisition is also used to analyze the signals, digitizing the signals and acquiring the signals from different inputs. The main drawbacks in data acquisition system are data storage, hardware size and remote monitoring. The System-on-Chip Field Programmable Gate Array (SoC-FPGA) is used in the proposed system in the aim to reduce the hardware and memory size. Further to provide remote monitoring with Ethernet/Wi-Fi, the Network Control Module (NCM) is integrated with Data acquisition and processing module for the communication between the systems. This developed system achieves high resolution with memory reduction, reduced hardware size, fast remote monitoring and control. It is used for real time processing in DAQ and signal processing. For fault tolerance and portability, the full system reconfigurability based FPGA acts as the best solution and the system can be reused with different configurations. The control of data acquisition and the subsequent management of data are coded in LabVIEW. LabVIEW tool is used to design and develop a four-channel Data Acquisition and Processing (DAQP) unit. National Instruments Data Acquisition (NIDAQ) and National Instruments Field Programmable Gate Array (NIFPGA) are used to test and implement the design for real time processing. This is designed to provide high accuracy, storage and portability.展开更多
The quality of a multichannel audio signal may be reduced by missing data, which must be recovered before use. The data sets of multichannel audio can be quite large and have more than two axes of variation, such as c...The quality of a multichannel audio signal may be reduced by missing data, which must be recovered before use. The data sets of multichannel audio can be quite large and have more than two axes of variation, such as channel, frame, and feature. To recover missing audio data, we propose a low-rank tensor completion method that is a high-order generalization of matrix completion. First, a multichannel audio signal with missing data is modeled by a three-order tensor. Next, tensor completion is formulated as a convex optimization problem by defining the trace norm of the tensor, and then an augmented Lagrange multiplier method is used for solving the constrained optimization problem. Finally, the missing data is replaced by alternating iteration with a tensor computation. Experiments were conducted to evaluate the effectiveness on data of a 5.1-channel audio signal. The results show that the proposed method outperforms state-of-the-art methods. Moreover, subjective listening tests with MUSHRA(Multiple Stimuli with Hidden Reference and Anchor) indicate that better audio effects were obtained by tensor completion.展开更多
文摘Normally, Data acquisition (DAQ) is used to acquire the signals from different devices like sensors, transducers, actuators etc. The data acquisition is also used to analyze the signals, digitizing the signals and acquiring the signals from different inputs. The main drawbacks in data acquisition system are data storage, hardware size and remote monitoring. The System-on-Chip Field Programmable Gate Array (SoC-FPGA) is used in the proposed system in the aim to reduce the hardware and memory size. Further to provide remote monitoring with Ethernet/Wi-Fi, the Network Control Module (NCM) is integrated with Data acquisition and processing module for the communication between the systems. This developed system achieves high resolution with memory reduction, reduced hardware size, fast remote monitoring and control. It is used for real time processing in DAQ and signal processing. For fault tolerance and portability, the full system reconfigurability based FPGA acts as the best solution and the system can be reused with different configurations. The control of data acquisition and the subsequent management of data are coded in LabVIEW. LabVIEW tool is used to design and develop a four-channel Data Acquisition and Processing (DAQP) unit. National Instruments Data Acquisition (NIDAQ) and National Instruments Field Programmable Gate Array (NIFPGA) are used to test and implement the design for real time processing. This is designed to provide high accuracy, storage and portability.
基金partially supported by the National Natural Science Foundation of China under Grants No. 61571044, No.61620106002, No.61473041, No.11590772, No.61640012Inner Mongolia Natural Science Foundation under Grants No. 2017MS(LH)0602
文摘The quality of a multichannel audio signal may be reduced by missing data, which must be recovered before use. The data sets of multichannel audio can be quite large and have more than two axes of variation, such as channel, frame, and feature. To recover missing audio data, we propose a low-rank tensor completion method that is a high-order generalization of matrix completion. First, a multichannel audio signal with missing data is modeled by a three-order tensor. Next, tensor completion is formulated as a convex optimization problem by defining the trace norm of the tensor, and then an augmented Lagrange multiplier method is used for solving the constrained optimization problem. Finally, the missing data is replaced by alternating iteration with a tensor computation. Experiments were conducted to evaluate the effectiveness on data of a 5.1-channel audio signal. The results show that the proposed method outperforms state-of-the-art methods. Moreover, subjective listening tests with MUSHRA(Multiple Stimuli with Hidden Reference and Anchor) indicate that better audio effects were obtained by tensor completion.
