-This paper presents our approach to modeling and prediction of session throughput of constant bit rate streams in wireless data networks. A stable traffic generator is used to generate smooth data streams that are transmitted across various types of wireless connections in real-world wireless data networks, including wireless LANs and wireless cellular WANs. The throughput values of the data s...

This paper investigated the ability of a hybrid time-delayed artificial neural network (TDANN)/autoregressive TDANN (AR-TDANN) to predict clenching movements during mastication from surface electromyography (SEMG) signals. Actual jaw motions and SEMG signals from the masticatory muscles were recorded and used as output and input, respectively. Three separate TDANNs/AR-TDANNs were used to predic...

w e ppose a new algorithm for enhancing noisy speech which have been degraded by statistically independent additive noise. The al p rithm is based upon modeling the clean speech as a hidden Markov process with mixtures of Gaussian autoregressive (AR) output processes, and the noise process as a sequence of stationary, statistically independent, Gaussian AR vectors. The parameter sets of the mod...

S U M M A R Y Recent studies show that the frequency content of continuous passive recordings contains useful information for the study of hydraulic fracturing experiments as well as longstanding applications in volcano and global seismology. The short-time Fourier transform (STFT) is usually used to obtain the time–frequency representation of a seismic trace. Yet, this transform has two main d...

This paper describes a method for estimating the parameters of an autoregressive (AR) process from a nite number of noisy measurements. The method uses a modi ed set of YuleWalker equations that lead to a quadratic eigenvalue problem which when solved, gives estimates of the AR parameters and the measurement noise variance. Version 2, submitted to IEEE Transactions on Signal Processing January ...

Long intermediate AR models are used in Durbin's algorithms for ARMA estimation. The order of that long AR model is infinite in the asymptotical theory, but very high AR orders are known to give inaccurate ARMA models in practice. A theoretical derivation is given for two different finite AR orders, as a function of the sample size. The first is the AR order optimal for prediction with a purely...