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We show that for a class of penalty functions, finding the global optimizer in the penalized least squares estimation is equivalent to the 'exact cover by 3-sets' problem, which belongs to a class of NP-hard problems. The NP-hardness result is then extended to the cases of penalized least absolute deviations regression and a special class of penalized(More)
This paper introduces the speech synthesis systems developed by USTC and iFlytek for Blizzard Challenge 2007. These two systems are both HMM-based ones and employ similar training algorithms, where contextual dependent HMMs for spectrum, F0 and duration are estimated according to the acoustic features and contextual information of training database.(More)
Multiuser multi-input multi-output orthogonal frequency division multiple access (MIMO-OFDMA) is regarded as an important technology for increasing the flexibility and efficiency of wireless communication systems. A well-behaved resource allocation strategy is crucial for the performance of such systems. In this paper, we systematically study the allocation(More)
Multi-user MIMO-OFDMA is regarded as an important technology for increasing the flexibility and efficiency of wireless communication systems. A well-behaved resource allocation strategy is crucial for the performance of such systems. In this paper, we study the allocation problem from a cooperative game theory perspective and present two algorithms to find(More)
—We consider the problem of optimal power allocation in a sensor network where the sensors observe a dynamic parameter in noise and coherently amplify and forward their observations to a fusion center (FC). The FC uses the observations in a Kalman filter to track the parameter, and we show how to find the optimal gain and phase of the sensor transmissions(More)
We consider a network of single-antenna sensors that observe an unknown deterministic parameter. Each sensor applies a phase shift to the observation and the sensors simultaneously transmit the result to a multi-antenna fusion center (FC). Based on its knowledge of the wireless channel to the sensors, the FC calculates values for the phase factors that(More)
—We consider the problem of optimal distributed beamforming in a sensor network where the sensors observe a dynamic parameter in noise and coherently amplify and forward their observations to a fusion center (FC). The FC uses a Kalman filter to track the parameter using the observations from the sensors, and we show how to find the optimal gain and phase of(More)
In recent years, radio positioning has received increasing attention and found many applications in various areas. However, the existence of non-line-of-sight (NLOS) paths introduces considerable positioning errors. In this paper, we propose a two-step approach in order to deal with pure NLOS scenarios based on a simple assumption regarding the propagation(More)
We consider the detection and estimation of a zero-mean Gaussian signal in a wireless sensor network with a coherent multiple access channel, when the fusion center (FC) is configured with a large number of antennas and the wireless channels between the sensor nodes and FC experience Rayleigh fading. For the detection problem, we study the Neyman-Pearson(More)