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In this paper, we first investigated two estimation issues of RF impairments: a saturation bias of nonlinearity estimates and limited resources for RF impairment estimation.
Second, several specification and estimation issues are poorly addressed in prior work, possibly generating biased results.
This paper considers the parameter estimation issues of an infinite impulse response (IIR) filter with colored noise which is treated as an autoregressive process.
This paper considers fault detection and estimation issues for a class of nonlinear systems with uncertainty, using an equivalent output error injection approach.
If the S-4 review process is effective, it should alleviate mispricing of goodwill and resolve accounting or estimation issues before they rise to the level of a restatement.
By utilizing both stochastic analysis and Lyapunov functional approach, we obtain a lot of sufficient conditions to ensure the desired H∞ performance, while the mean-square stability is also satisfied for this investigated state estimation issues of ANNs.
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Notably, the inherent parameters estimation issue emerging in the entire system greatly affects the overall network performance.
The estimation issue of the cyclic coherence is addressed in detail, as well as its use in a statistical test, and sub-optimal simplifications.
In this work, we study the quantized asynchronous dissipative state estimation issue for Markov jumping neural networks subject to randomly occurring sensor saturations.
In the first part of the paper, we address the channel estimation issue for DS-UWB receiver, in the presence of multi-user interference (MUI) and MB-OFDM interference within the framework of wireless personal area networks (WPANs).
In this paper, we will focus on the scale estimation issue of DCF-based visual tracking.
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CEO of Professional Science Editing for Scientists @ prosciediting.com