A LAW OF THE ITERATED LOGARITHM FOR NEAREST NEIGHBOR ESTIMATION OF MULTIVARIATE DENSITY FUNCTION

Let X be a d-dimensional random vector with unknown density function f(z) = f (z1, ..., z(d)), and let f(n) be teh nearest neighbor estimator of f proposed by Loftsgaarden and Quesenberry (1965). In this paper, we established the law of the iterated logarithm of f(n) for general case of d greater-than-or-equal-to 1, which gives the exact pointwise strong convergence rate of f(n).

Application of the Attenuation Correction Technology in C-band Radar Precipitation Estimation

[ Objective] The research aimed to study application of the attenuation correction technology in C-band radar precipitation estimation. [ Method~ Based on CINRAD-CB radar data in Shaanxi, we conducted the attenuation correction experiment by using iteration method and Kufa method respectively. Moreover, we conducted application expedment of the Kufa attenuation correction method in the quantitative precipitation esti- mation. [ Result~ Attenuation correction technology could compensate for attenuation problem of the echo at the distant range. Calculation result of the iteration method finally tended to that of the Kufa method. Moreover, iteration method spent more time. Therefore, Kufa attenuation correction technology was more suitable for business operation. When strong echo was near radar, generated attenuation was more obvious, and application value of the attenuation correction was bigger. Attenuation correction technology was used for quantitative precipitation estimation, which was favor- able for improving accuracy of the precipitation estimation. But we should conduct detailed planning on calculation scheme of the precipitation esti- mation because that different calculation schemes had great influences on accuracy of the quantitative precipitation estimation. [ Cendusien] This research provided a basis for improving accuracy of the quantitative precipitation estimation in Shaanxi. Key words Attenuation correction

水声FBMC-OQAM通信的时变信道估计与符号检测

Filter bank multicarrier(FBMC)systems with offset quadrature amplitude modulation(OQAM)need long data blocks to achieve high spectral efficiency.However,the transmission of long data blocks in underwater acoustic(UWA)communication systems often encounters the challenge of time-varying channels.This paper proposes a time-varying channel tracking method for short-range high-rate UWA FBMC-OQAM communication applications.First,a known preamble is used to initialize the channel estimation at the initial time of the signal block.Next,the estimated channel is applied to detect data symbols at several symbol periods.The detected data symbols are then reused as new pilots to estimate the next time channel.In the above steps,the unified transmission matrix model is extended to describe the time-varying channel input-output model in this paper and is used for symbol detection.Simulation results show that the channel tracking error can be reduced to less than−20 dB when the channel temporal coherence coefficient exceeds 0.75 within one block period of FBMC-OQAM signals.Compared with conventional known-pilot-based methods,the proposed method needs lower system overhead while exhibiting similar time-varying channel tracking performance.The sea trial results further proved the practicability of the proposed method.

The large sample property of the iterative generalized least squares estimation for hierarchical mixed effects model

In many fields, we need to deal with hierarchically structured data.For this kind of data, hierarchical mixed effects model can show the correlationof variables in the same level by establishing a model for regression coefficients.Due to the complexity of the random part in this model, seeking an effectivemethod to estimate the covariance matrix is an appealing issue. Iterative generalizedleast squares estimation method was proposed by Goldstein in 1986 and wasapplied in special case of hierarchical model. In this paper, we extend themethod to the general hierarchical mixed effects model, derive its expressions indetail and apply it to economic examples.

Performance Analysis of Hard Iterative Channel Estimation in Turbo Equalization

Reasonable bit error rate performance requires perfect channel state information （CSI） in traditional turbo equalization （TE）, which is hard to obtain in practice. Soft and hard iterative algorithms have been developed to address the channel estimation problem with the performance of the soft iteratwe channel estimate based on the recursive least square algorithm. This paper presents an analysis of the performance of hard iterative channel estimation （HICE） based on the least mean square algorithm. The analysis uses a cost function with the hard decision on the TE output. An iterative channel correction （ICC） algorithm based on the gradient descent algorithm is used to iteratively minimize the cost function. The simulation results agree with the theoretical lower bound for the mean square error （MSE） of the estimated channels. Simulations show that, given an imperfect CSI with an MSE below the upper bound, the linear minimum mean squared error TE （LMMSE-TE） using the ICC has only small performance degradation compared to that with a perfect CSI, while the traditional LMMSE-TE suffers from severe error floor effect even with more iterations.

Accuracy and Efficiency: The Comparison of Different RPC Parameters Solving Methods

As a generalized sensor, the RPC model with its accuracy equally matches the physical sensor model. Moreover, the accurate positioning combining with the flexibility in application leads the RPC model to be the priority in photogrammetry processing. Generally, the RPC model is calculated through a control grid. Different RPC parameters solving methods and the operation efficiency all serve as variables in the accuracy of the model. In this paper, the ridge estimation iterative method, spectrum correction iteration, and conjugate gradient method are employed to solve RPC parameters;the accuracy and efficiency of three solving methods are analyzed and compared. The results show that ridge estimation iterative method and spectrum correction iteration have obvious advantages in accuracy. The ridge estimation iterative method has fewer iteration times and time con-sumption, and spectrum correction iteration has more stable precision.