An iterative blind self-synchronizing MMSE receiver with a J-element antenna array for asynchronous DS-CDMA signals is developed in this paper. the primary requirement is knowledge of the desired user's signature ...
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ISBN:
(纸本)078037858X
An iterative blind self-synchronizing MMSE receiver with a J-element antenna array for asynchronous DS-CDMA signals is developed in this paper. the primary requirement is knowledge of the desired user's signature sequence. A computationally efficient IIR-filter version of the proposed receiver is developed that utilizes a correlation-subtraction architecture based on the multistage reduced-rank Wiener filter introduced by Goldstein and Reed. this technique eliminates the tasks of an explicit estimation of the covariance matrix and its inversion. Moreover, this multistage scheme achieves a rapid adaptive convergence and improves the tracking ability at a relatively small amount of observed data. these features contribute significantly to the reduction of the computational cost and make possible practical realization.
Data dimensionality reduction via linear embedding is a typical approach to economizing the computational cost of machine learning systems. In the context of sparse subspace clustering (SSC), this paper proposes a two...
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ISBN:
(数字)9781728119465
ISBN:
(纸本)9781728119472
Data dimensionality reduction via linear embedding is a typical approach to economizing the computational cost of machine learning systems. In the context of sparse subspace clustering (SSC), this paper proposes a two-step neighbor identification scheme using linear neighborhood-preserving embedding. In the first step, a quadratically- constrained ℓ 1 -minimization algorithm is solved for acquiring the side subspace neighborhood information, whereby a linear neighborhood-preserving embedding is designed accordingly. In the second step, a LASSO sparse regression algorithm is conducted for neighbor identification using the dimensionality- reduced data. the proposed embedding design explicitly takes into account the subspace neighborhood structure of the given data set. Computer simulations using real human face data show that the proposed embedding not only outperforms other existing dimensionality-reduction schemes but also improves the global data clustering accuracy when compared to the baseline solution without data compression.
We consider a multi-link multiple-input single-output interference channel. A link in this setting is noncooperative if its transmission does not take into account the interference it generates at other links. Noncoop...
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We consider a multi-link multiple-input single-output interference channel. A link in this setting is noncooperative if its transmission does not take into account the interference it generates at other links. Noncooperative operation of the links is generally not efficient. To improve this situation, we study link cooperation via coalitional games. In coalitional games, a player has an incentive to cooperate with other players if this improves his payoff. We model the setting as a game in coalitional form without transferable utility. the players (links) in a coalition either perform zero forcing transmission or Wiener filter precoding to each other. Necessary and sufficient conditions, in terms of a lower signal-to-noise ratio (SNR) threshold, are provided under which all players have the incentive to cooperate and form a grand coalition. In addition, we provide sufficient conditions under which all players have no incentive to cooperate. In this case, the SNR has to be below a specified SNR threshold. Hence, there exists an SNR range in which the links would profit in forming subcoalitions. therefore, we turn our attention to coalition formation games between the links. We utilize a coalition formation algorithm, called merge-and-split, to determine stable user grouping. Numerical results show that while in the low SNR regime noncooperation is efficient with single-player coalitions, in the high SNR regime all users benefit in forming a grand coalition. Coalition formation shows its significance in the mid SNR regime where subset user cooperation provides joint performance gains.
the size of an over complete dictionary seriously affects the computation speed of on-grid sparse algorithms. In the case of multi parameter estimation, the required dictionary size increases rapidly by multiplication...
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ISBN:
(数字)9781728119465
ISBN:
(纸本)9781728119472
the size of an over complete dictionary seriously affects the computation speed of on-grid sparse algorithms. In the case of multi parameter estimation, the required dictionary size increases rapidly by multiplication to ensure the accuracy of the results. therefore, it becomes infeasible to estimate all of the parameters directly by on-grid methods. In this paper, the feasible sparse spectrum fitting (SpSF) algorithm for computing boththe direction of arrival (DOA) and range estimation in collocated FDA-MIMO radars is introduced. Firstly, due to fact that a receive spatial frequency only depends on the angle, a covariance fitting technique for data preprocessing is adopted to reshape the data for DOA estimation. Next, the range is calculated in the transmit-receive spatial frequency domain by the SpSF algorithm. In addition, to improve the computational efficiency for an increased number of targets, the traditional convex optimization is replaced with a one-dimensional peak search approximation. Numerical simulations are carried out to verify the effectiveness of the proposed approach.
sensors sensitivities influence on signalprocessing quality is considered in the article. Different sensitivities cause interaction between additive and multiplicative errors. Parallel compensation structure is appli...
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sensors sensitivities influence on signalprocessing quality is considered in the article. Different sensitivities cause interaction between additive and multiplicative errors. Parallel compensation structure is applied. Classic approach is characterized and two unconventional approaches are proposed. Proposed approaches turn out to be more accurate than classic. Mathematical analysis of problem and experimental verification are presented.
A major difficulty in tracking unidentified vessels at sea is due to the need to observe large areas for long periods of time for sparsely appearing targets. A possible solution is to use a network of energy efficient...
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ISBN:
(纸本)9781509029211
A major difficulty in tracking unidentified vessels at sea is due to the need to observe large areas for long periods of time for sparsely appearing targets. A possible solution is to use a network of energy efficient underwater gliders that use buoyancy engines and are equipped withsensorarray, processing, and communication hardware. Gliders, however, have a limited size and payload which limits the length of their sensorarray and the capabilities of their power, processing, and communication modules. this reduces the resolution of measurements that can be collected and processed on board of gliders and be communicated to a fusion center for accurate target tracking. In this work, we propose the use of adaptive compressive sensing and processing to enable accurate target tracking while using low signal acquisition, processing, and communication rates, short sensorarray lengths, and simplified sensing and processing hardware hosted on gliders. Moreover, we propose a particle filtering method to fuse data from multiple sensing nodes and process sensorarray measurements with non-linear, non-Gaussian relationship to the target state. A simulation based scenario of tracking a single target by four underwater gliders is used to evaluate the effectiveness of the method.
this paper presents a distributed passive sonar system including a linear three hydrophones array used to acquire sounds and to perform the localization of the underwater acoustic source. the voltages of hydrophone...
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this paper presents a distributed passive sonar system including a linear three hydrophones array used to acquire sounds and to perform the localization of the underwater acoustic source. the voltages of hydrophone' channels are applied on the analog input of a multifunction I/O board that represent an important component of a distributed virtual measurement system that includes capabilities on acoustic signal acquisition and generation and advanced signalprocessing. Additional measurement channel associated with water quality monitoring is included in the system. PDA technology is also part of the work and is related withsignal generation for localization algorithm testing. Two GPS systems are used to localize a base and a remote measuring station during the localization tests. Related advanced signalprocessing is mentioned the developed wavelet filtering blocks for signal filtering and feature extraction as so as the neural network acoustic signal classifier.
A wireless sensor network employing multiple sensing and event detection modalities and distributed processing is proposed for smart home monitoring applications. Image sensing and vision-based reasoning are employed ...
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ISBN:
(纸本)1595934960
A wireless sensor network employing multiple sensing and event detection modalities and distributed processing is proposed for smart home monitoring applications. Image sensing and vision-based reasoning are employed to verify and further analyze events reported by other sensors. the system has been developed to address the growing application domain in caregiving to the elderly and persons in need of monitored living, who care to live independently while enjoying the assurance of timely access to caregivers when needed. An example of sensed events is the accidental fall of the person under care. A wireless badge node acts as a bridge between the user and the network. the badge node provides user-centric event sensing functions such as detecting falls, and also provides a voice communication channel between the user and the caregiving center when the system detects an alert and dials the center. the voice connection is carried over an ieee 802.15.4 radio link between the user badge and another node in the network that acts as a modem. Using signal strength measurements, the network nodes keep track of the approximate location of the user in the monitoring *** network also includes wall-mounted image sensor nodes, which are triggered upon detection of a fall to analyze their field-of-view and provide the caregiving center with further information about the user 's status. A description of the developed network and several examples of the vision-based reasoning algorithm are presented in the paper. Copyright 2006 ACM.
Directly transmitting the huge amount of typical hyperspectral data acquired on satellite to the ground station is inefficient. this paper proposes a new compressed sensing strategy for hyperspectral imagery on spaceb...
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ISBN:
(数字)9781728119465
ISBN:
(纸本)9781728119472
Directly transmitting the huge amount of typical hyperspectral data acquired on satellite to the ground station is inefficient. this paper proposes a new compressed sensing strategy for hyperspectral imagery on spaceborne sensors systems. As the onboard computing/storage resources are limited, e.g., on CubeSat, the measurement strategy should be computationally very light. Furthermore, considering the limited communication bandwidth, a very low sampling rate is desired. Our encoder accounts for these requirements by separately recording the spatial details and the spectral information, both of which essentially require only simple averaging operators. Our measurement strategy naturally induces a reconstruction criterion that can be elegantly interpreted as a well-known fusion problem in satellite remote sensing, allowing the adoption of a convex optimization method for simple and fast decoding. Our method, termed spatial/spectral compressed encoder (SPACE), is experimentally evaluated on real hyperspectral data, showing superior efficacy in terms of both sampling rate and reconstruction accuracy.
As is well known, the bilinear time-frequency distributions possesses a highly oscillatory cross term for each pair of signal terms. In this work, a novel method to suppress the cross-terms using beamforming is propos...
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ISBN:
(纸本)9781424427994
As is well known, the bilinear time-frequency distributions possesses a highly oscillatory cross term for each pair of signal terms. In this work, a novel method to suppress the cross-terms using beamforming is proposed. With Wigner-Ville Distribution as an example, the simulation results verify the feasibility of this method.
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