Brain-computer interface (BCI) actively translates the brain signals into executable actions by establishing direct communication between the human brain and external devices. Recording brain activity through electroencephalography (EEG) is generally contaminated with both physiological and nonphysiological artifacts, which significantly hinders the BCI performance. Artifact subspace reconstruction (ASR) is a well-known statistical technique that automatically removes artifact components by determining the rejection threshold based on the initial reference EEG segment in multichannel EEG recordings. In real-world applications, the fixed threshold may limit the efficacy of the artifact correction, especially when the quality of the reference data is poor. This study proposes an adaptive online ASR technique by integrating the Hebbian/anti-Hebbian neural networks into the ASR algorithm, namely, principle subspace projection ASR (PSP-ASR) and principal subspace whitening ASR (PSW-ASR) that segmentwise self-organize the artifact subspace by updating the synaptic weights according to the Hebbian and anti-Hebbian learning rules. The effectiveness of the proposed algorithm is compared to the conventional ASR approaches on benchmark EEG dataset and three BCI frameworks, including steady-state visual evoked potential (SSVEP), rapid serial visual presentation (RSVP), and motor imagery (MI) by evaluating the root-mean-square error (RMSE), the signal-to-noise ratio (SNR), the Pearson correlation, and classification accuracy. The results demonstrated that the PSW-ASR algorithm effectively removed the EEG artifacts and retained the activity-specific brain signals compared to the PSP-ASR, standard ASR (Init-ASR), and moving-window ASR (MW-ASR) methods, thereby enhancing the SSVEP, RSVP, and MI BCI performances. Finally, our empirical results from the PSW-ASR algorithm suggested the choice of an aggressive cutoff range of c = 1-10 for activity-specific BCI applications and a moderate range of for the benchmark dataset and general BCI applications.

Implementing a belief propagation (BP) based LDPC decoder requires high degrees of parallelism using many component soft-in soft-output (SISO) decoding units to perform message passing from variable nodes to check nodes or vice versa. An obvious complexity-reduction solution is to serialize the decoding process, i.e., dividing a decoding iteration into several serial sub-iterations in which a sub-iteration performs only part of the complete parallel message-passing operation. The group horizontal shuffled BP (GHSBP) and vertical shuffled BP (GVSBP) algorithms respectively partition the check and variable nodes of the code graph into groups to perform group-by-group message-passing decoding. This paper proposes new techniques to improve three key elements of a GHSBP decoding algorithm, namely, the grouping method, the decoding schedule and the log-likelihood updating formulae. The (check nodes) grouping method and decoding schedule optimize certain design criterion. The new normalized min-sum updating formula with a self-adjustable correction (scaling) factor offers better nonlinear approximation. Numerical performance of new GHSBP algorithms that include part or all three new techniques indicate that the combination of the proposed grouping and decoding schedule yields a faster convergence rate and our modified min-sum algorithm gives performance superior to that of the conventional min-sum and normalized min-sum algorithm and is very close to that of the sum-product algorithm.

Abstract Multimedia transmissions are delay‐sensitive Internet applications. Because mobile stations are in continual motion, handoff processes are necessary and unavoidable in wireless network environments. Because handoff processes tend to break the communication link, the research has been conducted on reducing the break time and arrival delay during Internet multimedia applications. In this paper, we propose an approach based on Fuzzy Logic to evaluate the average variation in signal strength received by a mobile station and produce a FitAP factor. This factor indicates the possible handoff access point that is suitable for the mobile station. According to the FitAP factor, a mobile station needs only to execute an active scan process once. Therefore, smaller handoff latency is expected. We compare the results from the current cell search scheme with that of the Fuzzy Logic approach. The statistical results show that the proposed method outperforms the current cell search scheme with an improved handoff latency performance. Copyright © 2007 John Wiley & Sons, Ltd.

PIM multicast network is very convenient and can be fully applied in applications that provide one-to-many services, such as video conference, online games and real time voice stream, etc. The key point is the share tree environment formed by Rendezvous Point (RP) and Core node. When RP node fails, the share tree network will solve the crash. In this paper, an efficient bootstrap router (BSR) based RP mechanism was proposed to solve the RP recovery problem in share tree network of PIM while the RP fails.

We study the decoding of product codes and a class of parallel concatenated product codes (PCPC). PCPC improves the minimum distance while retaining the merit of low decoding complexity of turbo product codes (TPC). We prove that using the Fibonacci interleaver does help increasing the minimum distance. The regularity of the interleaver also reduces the implementation complexity and makes parallel interleaving feasible. We show that Pyndiah's algorithm for decoding product codes produce an annealing effect similar to that of the so-called annealed belief propagation (ABP) algorithms which adjusts the "temperature" of an augmented cost surface. Decoding methods based on modified Pyndiah and annealed BCJR algorithms for both PC and PCPC are proposed and their performance is compared.

Multimedia transmissions are delay sensitive Internet applications. Because mobile stations move all of the time, handoff processes are necessary and unavoidable in wireless network environments. Since handoff processes tend to break the communication link, some researches have been done to reduce the break time and arrival delay during Internet multimedia applications. In this paper, we propose an approach based on fuzzy logic to evaluate the average and variation in signal strength received by a mobile station. According to our investigation, a mobile station needs to execute an active scan process only once to obtain the complete handoff parameters. Therefore, smaller handoff latency is expected

The paper studies two methods for detecting and removing channel error patterns in images transmitted by two-dimensional differential-pulse-code-modulation (2-D DCM) with fixed-length words. The methods are based on statistical classification and filtering procedures. For the predictions A+(C-B)/2 and A+(D-B)/2 in combination with 4-b DPCM, it is demonstrated experimentally by computer simulation that the effect of channel errors can effectively be reduced at bit-error rates (BERs) up to approximately 0.1%.