Related papers: Unsupervised and Non Parametric Iterative Soft Bit…
Novel bitwise retransmission schemes are devised which retransmit only the bits received with small reliability. The retransmissions are used to accumulate the reliabilities of individual bits. Unlike the conventional automatic repeat…
The performances of automatic speech recognition (ASR) systems are usually evaluated by the metric word error rate (WER) when the manually transcribed data are provided, which are, however, expensively available in the real scenario. In…
This paper presents a distributed estimator for a deterministic parametric physical field sensed by a homogeneous sensor network and develops a new transformed expression for the Cramer-Rao lower bound (CRLB) on the variance of distributed…
This letter investigates performance enhancement by the concept of multi-carrier index keying in orthogonal frequency division multiplexing (OFDM) systems. For the performance evaluation, a tight closed-form approximation of the bit error…
This paper investigates the finite sample performance of a range of parametric, semi-parametric, and non-parametric instrumental variable estimators when controlling for a fixed set of covariates to evaluate the local average treatment…
In this work, an integrated performance evaluation of a decode-and-forward (DF) multi-hop wireless communication system is undertaken over the non-linear generalized $\alpha-\kappa-\mu$ and $\alpha-\kappa-\mu$-Extreme fading models.…
We consider estimating the density of a response conditioning on an error-prone covariate. Motivated by two existing kernel density estimators in the absence of covariate measurement error, we propose a method to correct the existing…
This paper presents an analysis of how to calculate bit error ratio (BER) with physical explanation for optically pre-amplified DPSK receivers using optical Mach-Zehnder interferometer (MZI) demodulation and balanced detection. It is shown…
Nonparametric kernel density and local polynomial regression estimators are very popular in Statistics, Economics, and many other disciplines. They are routinely employed in applied work, either as part of the main empirical analysis or as…
The present study proposes incorporating non-parametric knowledge into the diffusion least-mean-squares algorithm in the framework of a maximum a posteriori (MAP) estimation. The proposed algorithm leads to a robust estimation of an unknown…
We address photon-number-assisted, polarization- based, binary communication systems equipped with photon counting receivers. In these channels information is encoded in the value of polarization phase-shift but the carrier has and…
Mutual Information (MI) is a crucial measure for capturing dependencies between variables, but exact computation is challenging in high dimensions with intractable likelihoods, impacting accuracy and robustness. One idea is to use an…
In the area of basic and network coded cooperative communication, the expected end-to-end bit error rate (BER) values are frequently required to compare the proposed coding, relaying, and decoding techniques. Instead of obtaining these…
We investigate a data-driven approach to constructing uncertainty sets for robust optimization problems, where the uncertain problem parameters are modeled as random variables whose joint probability distribution is not known. Relying only…
In this paper, we study the Bernstein polynomial model for estimating the multivariate distribution functions and densities with bounded support. As a mixture model of multivariate beta distributions, the maximum (approximate) likelihood…
In this work we design a receiver that iteratively passes soft information between the channel estimation and data decoding stages. The receiver incorporates sparsity-based parametric channel estimation. State-of-the-art sparsity-based…
This paper presents a model selection technique of estimation in semiparametric regression models of the type Y_i=\beta^{\prime}\underbarX_i+f(T_i)+W_i, i=1,...,n. The parametric and nonparametric components are estimated simultaneously by…
This paper is a study of non-linear effects of RF Amplifiers on Communication Systems Performance. High speed data communication is made possible by Multilevel Modulation schemes. This paper presents a study of these non linear effects on…
In nonparametric regression analysis, errors are possibly correlated in practice, and neglecting error correlation can undermine most bandwidth selection methods. When no prior knowledge or parametric form of the correlation structure is…
The Bayes error rate (BER) is a fundamental concept in machine learning that quantifies the best possible accuracy any classifier can achieve on a fixed probability distribution. Despite years of research on building estimators of lower and…