Content based error resilience coding using redundant coding, reference frame modification, and mode decision

Quality degradation occurs during transmission of video streaming over the error-prone network. By jointly using redundant slice, reference frame selection, and intra/inters mode decision, a content and end-to-end rate-distortion based error resilience method is proposed. Firstly, the intra/inter mode decision is implemented using macro-block(MB) refresh, and then redundant picture and reference frame selection are utilized together to realize the redundant coding. The estimated error propagation distortion and bit consumption of refresh MB are used for the mode and reference frame decision of refresh MB. Secondly, by analyzing the statistical property in the successive frames, the error propagation distortion and bit consumption are formulated as a function of temporal distance. Encoding parameters of the current frame is determined by the estimated error propagation distortion and bit consumption. Thirdly, by comparing the rate-distortion cost of different combinations, proper selection of error resilience method is performed before the encoding process of the current frame. Finally, the MB mode and bit distribution of the primary picture are analyzed for the derivation of the texture information. The motion information is subsequently incorporated for the calculation of video content complexity to implement the content based redundant coding. Experimental results demonstrate that the proposed algorithm achieves significant performance gains over the LA-RDO and HRP method when video is transmitted over error-prone channel.

EFFICIENT DESIGN OF ANTI-JAMMING RATELESS CODING IN COGNITIVE OFDM

Efficient anti-jamming rateless coding based on cognitive Orthogonal Frequency Division Multiplexing (OFDM) modulation in Cognitive Radio Network (CRN) is mainly discussed. Rateless coding with small redundancy and low complexity is presented, and the optimal design methods of building rateless codes are also proposed. In CRN, anti-jamming rateless coding could recover the lost packets in parallel channels of cognitive OFDM, thus it protects Secondary Users (SUs) from the in-terference by Primary Users (PUs) efficiently. Frame Error Rate (FER) and throughput performance of SU employing anti-jamming rateless coding are analyzed in detail. Performance comparison between rateless coding and piecewise coding are also presented. It is shown that, anti-jamming rateless coding provides low FER and Word Error Rate (WER) performance with uniform sub-channel selection. Meanwhile, it is also verified that, in higher jamming rate and longer code redundancy scenario, rateless coding method could achieve better FER and throughput performance than another anti-jamming coding schemes.

A Novel Frame Error Concealment Scheme Based on Gain Control for TCX Audio Codec

A novel frame error concealment scheme is proposed to improve the decoded audio quality of the receiver for transform coded excitation（TCX）audio codec.This scheme,which is a gain control approach based on the stability of linear predictive coding（LPC）filter,predicts the lost frames by utilizing the linear spectrum frequency and different continuous attenuation factor of different kinds of lost frames.Signal noise ratio（SNR）test and multiple stimuli with hidden reference and anchor（MUSHRA）test are conducted to evaluate the performance of this approach in adaptive multi-rate wideband plus（AMR-WB＋）audio codec.Compared with the original frame error concealment scheme,our scheme achieves better audio recovery quality in AMR-WB＋audio codec.

Non-sampling errors in questionnaire surveys: findings from a National Fertility Survey

Non-sampling errors can generally be divided into three types:sampling frame errors,non-response errors and measurement errors.Missing target units in the sam-pling frame,improper handling of non-responses,and misreporting or underreport-ing of key variables in the questionnaire can all cause deviations in a survey’s results.The widespread application of Computer-Assisted Personal Interviewing(CAPI)systems and the inclusion of administrative records from government sources in sur-veys has strengthened the ability to control non-sampling errors.Taking a national fertility sampling survey as an example,this study summarizes the sources of var-ious non-sampling errors and explains how to harness big data resources such as administrative records to control non-sampling errors throughout the survey.The study analyzes the impact of three types of non-sampling errors on the results of the fertility survey and examines the strategies used to address the problems caused by these non-sampling errors.The findings indicate that non-sampling errors were the main source of total error in the survey,and that the errors found came mainly from sampling frame errors;non-response errors and measurement errors were controlled and had little impact on the survey results.