Detection of the speaker position is a crucial task in hands-free speech recognition applications. In this paper we present a novel speech beam-former for noisy environments. Initially, the localization algorithm extr...
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ISBN:
(纸本)0780374029
Detection of the speaker position is a crucial task in hands-free speech recognition applications. In this paper we present a novel speech beam-former for noisy environments. Initially, the localization algorithm extracts a set of candidate directions of the signal sources using array signal processing methods in the frequency domain. Then, a minimum variance (MV) beam-former identifies the speech signal in the direction where the signal's spectrum entropy is minimized, The proposed method is evaluated by a phoneme recognition system using noise recordings from an air-condition fan and the TIMIT speech corpus. Extended experiments, carried out in the range of 25-0 dB, show almost perfect estimation of the speaker DOA in all cases. As a consequence, the recognition rate increases significantly compared to the rate obtained by a single microphone. The recognition improvement increases especially in very low SNRs.
localization is one of the oldest mathematical and technical problems that have been at the forefront of research and development for decades. In a wireless sensor network (WSN), nodes are not able to recognize their ...
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localization is one of the oldest mathematical and technical problems that have been at the forefront of research and development for decades. In a wireless sensor network (WSN), nodes are not able to recognize their position. To solve this problem, studies have been done on algorithms to achieve accurate estimation of nodes in WSNs. In this paper, we present an improvement of a localization algorithm namely Gaussian mixture semi-definite programming (GM-SDP-2). GM -SDP is based on the received signal strength (RSS) to achieve a maximum likelihood location estimator. The improvement lies in the placement of anchors through the Fuzzy C-Means clus-tering method where the cluster centers represent the anchors' positions. The simulation of the algorithm is done in Matlab and is based on two evaluation metrics, namely normalized root-mean-squared error (RMSE) and cumulative distribution function (CDF). Simulation results show that our improved algorithm achieves better performance compared to those using a predetermined placement of anchors.
The lifespan assessment and maintenance planning of high-voltage power systems requires condition monitoring of all the operational equipment in a specific area. Electrical insulation of electrical apparatuses is pron...
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The lifespan assessment and maintenance planning of high-voltage power systems requires condition monitoring of all the operational equipment in a specific area. Electrical insulation of electrical apparatuses is prone to failure due to high electrical stresses, and thus it is a critical aspect that needs to be monitored. The ageing process of the electrical insulation in high voltage equipment may accelerate due to the occurrence of partial discharge (PD) that may in turn lead to catastrophic failures if the related defects are left untreated at an initial stage. Therefore, there is a requirement to monitor the PD levels so that an unexpected breakdown of high-voltage equipment is avoided. There are several ways of detecting PD, such as acoustic detection, optical detection, chemical detection, and radiometric detection. This paper focuses on reviewing techniques based on radiometric detection of PD, and more specifically, using received signal strength (RSS) for the localization of faults. This paper explores the advantages and disadvantages of radiometric techniques and presents an overview of a radiometric PD detection technique that uses a transistor reset integrator (TRI)-based wireless sensor network (WSN).
The design problems of localization algorithm, distribution density estimation and node's moving path for data collection in multi-layers mobile wireless senor network are investigated. To ensure estimating accura...
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ISBN:
(纸本)9781424462520
The design problems of localization algorithm, distribution density estimation and node's moving path for data collection in multi-layers mobile wireless senor network are investigated. To ensure estimating accurately the node density, this paper proposes a new movement control strategy for fusion nodes based on probabilistic coverage model. This method completed the unknown node localization through beacon nodes traversing the monitoring area, and estimated distribution density of nodes in the network based on probabilistic coverage model, and divided the nodes into groups as little as possible, and constructed the short path of the fusion node's data collection according to the centers of these limited groups. The results of the experiments indicated that the control policy of mobile fusion nodes can reduce greatly network energy, and prolong network lifetime.
In this paper, we design the source precoding matrices and the relay amplifying matrix of an amplify-and-forward multiuser multiple-input multiple-output (MIMO) relay communication system. The minimum mean-squared err...
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ISBN:
(纸本)9781424479078
In this paper, we design the source precoding matrices and the relay amplifying matrix of an amplify-and-forward multiuser multiple-input multiple-output (MIMO) relay communication system. The minimum mean-squared error (MSE) is taken as the design criterion. We propose an alternating technique to efficiently solve the nonconvex source and relay optimization problem. It is shown that both the optimal source and relay matrices have a beamforming structure. Simulation results demonstrate that the proposed source and relay design algorithms perform much better than the existing techniques in terms of both MSE and bit-error-rate.
Due to the highly hostile and unpredictable underwater environments, some beacon nodes in Underwater Wireless Sensor Networks (UWSNs) tend to move or be damaged. Therefore, the unknown nodes will be positioned with la...
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ISBN:
(纸本)9781509017812
Due to the highly hostile and unpredictable underwater environments, some beacon nodes in Underwater Wireless Sensor Networks (UWSNs) tend to move or be damaged. Therefore, the unknown nodes will be positioned with larger error, which abases the value of data collected by sensor nodes. In order to solve the beacon error problem, this paper proposes an error beacon filtering algorithm based on K-means clustering. Firstly, the position of each beacon is calculated by an improved trilateration method, and then the beacon with the maximum positioning error is filtered out through K-means clustering algorithm. Simulation results suggest that this algorithm can detect almost all error beacons effectively.
This paper describes the prototype of a decision support system oriented to air pollution network designers. The purpose is to help the users in the choice of the number and localization of instruments in an assigned ...
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Analyzing the measuring errors of nodes using Received Signal Strength Indications (RSSI) method, such as the parameter error of RSSI theoretical model and the obstacle error between neighbor nodes, this paper propose...
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ISBN:
(纸本)9781424421138
Analyzing the measuring errors of nodes using Received Signal Strength Indications (RSSI) method, such as the parameter error of RSSI theoretical model and the obstacle error between neighbor nodes, this paper proposed a localization algorithm based on analyzing of RSSI errors in wireless sensor networks called ERSSI. Based on the two errors mentioned, it got the online parameter changing method for RSSI theoretical model and reduced the effect of those small obstacles. We show by both theoretical analysis and simulations that this algorithm can get low localization errors when the size of obstacles is small.
Noise reduction algorithms have been proposed that try to imitate some aspects of the binaural information processing in the human hearing system by using two microphones at both ears and a central processor. Based on...
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ISBN:
(纸本)0780374029
Noise reduction algorithms have been proposed that try to imitate some aspects of the binaural information processing in the human hearing system by using two microphones at both ears and a central processor. Based on a two channel input, it is theoretically possible to cancel one interfering directional noise source at a time. Due to the relatively large distance between microphones, it should additionally be possible to detect and cancel reverberation based on coherence measures. In practice however, no significant increase in speech intelligibility has been shown so far with these schemes in acoustically complex environments characterized by diffuse noise and reverberation. This paper summarizes these results for a review. Furthermore, a localization algorithm is introduced, which uses a statistical description of the binaural signal differences in order to increase the robustness in estimating sound source incident directions in noisy environments. Possible noise reduction schemes based on this localization algorithm are discussed.
Compared with a single drone, the bee swarm unmanned aerial vehicles(UAVs) have a higher fault tolerance and mission accomplished rate. However, When the UAVs under a complex environment with electromagnetic interfere...
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ISBN:
(纸本)9781510640702
Compared with a single drone, the bee swarm unmanned aerial vehicles(UAVs) have a higher fault tolerance and mission accomplished rate. However, When the UAVs under a complex environment with electromagnetic interference, the communication connections will be interfered greatly, so the position information exchanging unable to work normally. The ultraviolet communication in this article has the advantages of non-line-of-sight, all-weather, and strong anti-interference ability. The structure of the ultraviolet beacon is designed to improve the communication quality and positioning capabilities of the bee swarm UAVs in electromagnetic interference. By building a flight guidance tracking error model and improving the performance of leader-follower algorithm, it is possible to solve the issue of large error feedback during the assembly of bee swarm UAVs. Finally, through simulation experiments to verify the accuracy of the above analysis.
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