With the ubiquitous application of Internet and wireless networks, H.264 video communication becomes more and more common. However, due to the high-efficiently predictive coding and the variable length entropy coding, it is more sensitive to transmission errors. The current error concealment (EC) scheme, which utilizes the spatial and temporal correlations to conceal the corrupted region, produces unsatisfied boundary artifacts. In this paper, first we propose variable block size error concealment (VBSEC) scheme inspired by variable block size motion estimation (VBSME) in H.264. This scheme provides four EC modes and four sub-block partitions. The whole corrupted macro-block (MB) will be divided into variable block size adaptively according to the actual motion. More precise motion vectors (MV) will be predicted for each sub-block. Then MV refinement (MVR) scheme is proposed to refine the MV of the heterogeneous sub-block by utilizing three step search (TSS) algorithm adaptively. Both VBSEC and MVR are based on our directional spatio-temporal boundary matching algorithm (DSTBMA). By utilizing these schemes, we can reconstruct the corrupted MB in the inter frame more accurately. The experimental results show that our proposed scheme can obtain better objective and subjective EC quality, respectively compared with the boundary matching algorithm (BMA) adopted in the JM11.0 reference software, spatio-temporal boundary matching algorithm (STBMA) and other comparable EC methods.

Harmonic balance (HB) method is well known principle for analyzing periodic oscillations on nonlinear networks and systems. Because the HB method has a truncation error, approximated solutions have been guaranteed by error bounds. However, its numerical computation is very time-consuming compared with solving the HB equation. This paper proposes an algebraic representation of the error bound using Grobner base. The algebraic representation enables to decrease the computational cost of the error bound considerably. Moreover, using singular points of the algebraic representation, we can obtain accurate break points of the error bound by collisions.

In this paper we analytically investigate the generalization performance of learning using correlated inputs in the framework of on-line learning with a statistical mechanical method. We consider a model composed of linear perceptrons with Gaussian noise. First, we analyze the case of the gradient method. We analytically clarify that the larger the correlation among inputs is or the larger the number of inputs is, the stricter the condition the learning rate should satisfy is, and the slower the learning speed is. Second, we treat the block orthogonal projection learning as an alternative learning rule and derive the theory. In a noiseless case, the learning speed does not depend on the correlation and is proportional to the number of inputs used in an update. The learning speed is identical to that of the gradient method with uncorrelated inputs. On the other hand, when there is noise, the larger the correlation among inputs is, the slower the learning speed is and the larger the residual generalization error is.

This paper presents the processor architecture which provides much higher level dependability than the current ones. The features of it are: (1) fault tolerance and secure processing are integrated into a modern superscalar VLSI processor; (2) light-weight effective soft-error tolerant mechanisms are proposed and evaluated; (3) timing errors on random logic and registers are prevented by low-overhead mechanisms; (4) program behavior is hidden from the outer world by proposed address translation methods; (5) information leakage can be avoided by attaching policy tags for all data and monitoring them for each instruction execution; (6) injection attacks are avoided with much higher accuracy than the current systems, by providing tag trackings; (7) the overall structure of the dependable processor is proposed with a dependability manager which controls the detection of illegal conditions and recovers to the normal mode; and (8) an FPGA-based testbed system is developed where the system clock and the voltage are intentionally varied for experiment. The paper presents the fundamental scheme for the dependability, elemental technologies for dependability and the whole architecture of the ultra dependable processor. After showing them, the paper concludes with future works.

This letter presents a new mathematical expression for the excess mean-square error (EMSE) of the affine projection (AP) algorithm. The proposed expression explicitly shows the proportional relationship between the EMSE and the condition number of the input signals.

This letter proposes a novel scheme of joint antenna combination and symbol detection in multi-input multi-output (MIMO) systems, which simultaneously determines the antenna combination coefficients to lower the RF chains and designs the minimum bit error rate (MBER) detector to mitigate the interference. The joint decision statistic, however, is highly nonlinear and the particle swarm optimization (PSO) algorithm is employed to reduce the computational overhead. Simulations show that the new approach yields satisfactory performance with reduced computational overhead compared with pervious works.

In this paper, the statistical characteristic of the Error Detection Delay (EDD) of Finite Precision Binary Arithmetic Codes (FPBAC) is discussed. It is observed that, apart from the probability of the Forbidden Symbol (FS) inserted into the list of the source symbols, the probability of the source sequence and the operation precision as well as the position of the FS in the coding interval can affect the statistical characteristic of the EDD. Experiments demonstrate that the actual distribution of the EDD of FPBAC is quite different from the geometric distribution of infinite precision arithmetic codes. This phenomenon is researched deeply, and a new statistical model (gamma distribution) of the actual distribution of the EDD is proposed, which can make a more precise prediction of the EDD. Finally, the relation expressions between the parameters of gamma distribution and the related factors affecting the distribution are given.

Combining relaying and multi-input multi-output (MIMO) transmission is a generic way to overcome the channel-fading impairments. Best antenna selection is a simple but efficient MIMO method that achieves the full diversity and also serves as a lower bound reference of MIMO performance. For a dual-hop MIMO system with an ideal amplify-and-forward (AF) relaying gain and best antenna selection, we provide a probability density function (PDF) of received signal-to-noise ratio (SNR) and an analytic BER equation when using M-ary PSK in Rayleigh fading channels. The analytic result is shown to exactly match with simulated one. Furthermore, the effect of link unbalance between the first hop and the second hop, due to differences in the number of antennas deployed in both hops as well as in the average power of channel coefficients, on the BER performance is numerically investigated and the results show that the links with better balance give better performance.

In this paper, a robust sound source localization approach is proposed. The approach retains good performance even when model errors exist. Compared with previous work in this field, the contributions of this paper are as follows. First, an improved broad-band and near-field array model is proposed. It takes array gain, phase perturbations into account and is based on the actual positions of the elements. It can be used in arbitrary planar geometry arrays. Second, a subspace model errors estimation algorithm and a Weighted 2-Dimension Multiple Signal Classification (W2D-MUSIC) algorithm are proposed. The subspace model errors estimation algorithm estimates unknown parameters of the array model, i.e., gain, phase perturbations, and positions of the elements, with high accuracy. The performance of this algorithm is improved with the increasing of SNR or number of snapshots. The W2D-MUSIC algorithm based on the improved array model is implemented to locate sound sources. These two algorithms compose the robust sound source approach. The more accurate steering vectors can be provided for further processing such as adaptive beamforming algorithm. Numerical examples confirm effectiveness of this proposed approach.

The H.264/AVC standard provides several new error-resilient features to enable the reliable transmission of compressed video signals over lossy packet networks. Flexible Macroblock Ordering (FMO) is one of the most interesting resilient features within the H.264/AVC standard. Unlike former standards, in which slices were constructed out of consecutive raster scan macroblocks, FMO suggests new slices composed of spatially distributed Macroblocks (MBs), and organized in a mixed-up fashion. H.264/AVC specifies seven types of FMO. The standard defines also an explicit FMO type (Type 6), which allows explicitly assignment of each MB within the frame to any available slice groups. Therefore new FMO types can be used and integrated into H264/AVC without violating the standard. In this paper we propose a new Explicit Chessboard-Wipe (ECW) Flexible Macroblocks Ordering (FMO) technique, which outperforms all other FMO types. The new ECW ordering results in effective error scattering which maximizes the number of correctly received macroblocks located around corrupted macroblocks, leading to better error concealment. Performance evaluations demonstrate that the proposed Explicit FMO approach outperforms all the FMO types. Both subjective and objective visual quality comparative study has been also carried out in order to validate the proposed approach.

In time-varying channels, the channel state information available at the transmitter (CSIT) is outdated due to inherent time delay between the uplink channel estimation and the downlink data transmission in TDD systems. In this letter, we propose an iterative precoding method and a linear decoding method which are both based on minimum mean-squared error (MMSE) criteria to mitigate the interference among data streams and users created by outdated CSIT for multiuser MIMO downlink systems. Analysis and simulation results show that the proposed method can effectively reduce the impairment of the outdated CSIT and improve the system capacity.

In this paper, we investigate the performance of maximum ratio combining (MRC) in the presence of multiple cochannel interferences over a flat Rayleigh fading channel. Closed-form expressions of signal-to-interference-plus-noise ratio (SINR), outage probability, and average symbol error rate (SER) of quadrature amplitude modulation (QAM) with M-ary signaling are obtained for unequal-power interference-to-noise ratio (INR). We also provide an upper-bound for the average SER using moment generating function (MGF) of the SINR. Moreover, we quantify the array gain loss between pure MRC (MRC system in the absence of CCI) and MRC system in the presence of CCI. Finally, we verify our analytical results by numerical simulations.

The main idea in perceptual image compression is to remove the perceptual redundancy for representing images at the lowest possible bit rate without introducing perceivable distortion. A certain amount of perceptual redundancy is inherent in the color image since human eyes are not perfect sensors for discriminating small differences in color signals. Effectively exploiting the perceptual redundancy will help to improve the coding efficiency of compressing color images. In this paper, a locally adaptive perceptual compression scheme for color images is proposed. The scheme is based on the design of an adaptive quantizer for compressing color images with the nearly lossless visual quality at a low bit rate. An effective way to achieve the nearly lossless visual quality is to shape the quantization error as a part of perceptual redundancy while compressing color images. This method is to control the adaptive quantization stage by the perceptual redundancy of the color image. In this paper, the perceptual redundancy in the form of the noise detection threshold associated with each coefficient in each subband of three color components of the color image is derived based on the finding of perceptually indistinguishable regions of color stimuli in the uniform color space and various masking effects of human visual perception. The quantizer step size for the target coefficient in each color component is adaptively adjusted by the associated noise detection threshold to make sure that the resulting quantization error is not perceivable. Simulation results show that the compression performance of the proposed scheme using the adaptively coefficient-wise quantization is better than that using the band-wise quantization. The nearly lossless visual quality of the reconstructed image can be achieved by the proposed scheme at lower entropy.

Configurable clock is necessary for many applications such as digital communication systems, however, using the conventional direct digital frequency synthesizer (DDS) as a pulse or clock generator may cause jitter problems. People usually employ phase-interpolation approaches to generate a pulse or clock with correct time intervals. This work proposes a new phase-interpolation DDS scheme, which uses the output of the phase accumulator to provide an initial voltage on an integration capacitor by pre-charging in the first phase, and then performs integration operation on the same integration capacitor in the second phase. By using single capacitor integration, the instability of the delay generator existed in the phase-interpolation DDS can be avoided, and the impact caused by capacitance error in the circuit implementation also can be reduced. Furthermore, without ROM tables, the proposed DDS using pre-charging integration not only reduces the spurious level of the clock output, but also has a low hardware complexity.

This paper proposes a new MIMO-OFDM precoding technique that aims to minimize a bit error rate (BER) upper bound of the maximum likelihood detection (MLD) in mobile radio communications. Using a steepest descent algorithm, the proposed method estimates linear precoding matrices that can minimize the upper bound of BER under power constraints. Since the upper bound is derived from all the pairwise error probabilities, this method can effectively optimize overall Euclidean distances between signals received by multiple antennas and their replicas. Computer simulations evaluate the BER performance and channel capacity of the proposed scheme for 22 and 44 MIMO-OFDM systems with BPSK, QPSK, and 16 QAM. It is demonstrated that the proposed precoding technique is superior in terms of average BER to conventional precoding methods including a precoder which maximizes only the minimum Euclidean distance as the worst case.

A reversible watermark algorithm with large capacity has been developed by applying the difference expansion of a generalized integer transform. In this algorithm, a watermark signal is inserted in the LSB of the difference values among pixels. In this paper, we apply the prediction errors calculated by a predictor in JPEG-LS for embedding watermark, which contributes to increase the amount of embedded information with less degradation. As one of the drawbacks discovered in the above conventional method is the large size of the embedded location map introduced to make it reversible, we decrease the large size of the location map by vectorization, and then modify the composition of the map using the local characteristics. We also exclude the positions such that the modification in the embedding operation cannot increase the capacity but merely degrade the image quality, which can be applicable to the conventional methods.

As technology scales down, leakage energy accounts for a greater proportion of total energy. Applying the drowsy technique to a cache, is regarded as one of the most efficient techniques for reducing leakage energy. However, it increases the Soft Error Rate (SER), thus, many researchers doubt the reliability of the drowsy technique. In this paper, we show several reasons why the instruction cache can adopt the drowsy technique without reliability problems. First, an instruction cache always stores read-only data, leading to soft error recovery by re-fetching the instructions from lower level memory. Second, the effect of the re-fetching caused by soft errors on performance is negligible. Additionally, a considerable percentage of soft errors can occur without harming the performance. Lastly, unrecoverable soft errors can be controlled by the scrubbing method. The simulation results show that the drowsy instruction cache rarely increases the rate of unrecoverable errors and negligibly degrades the performance.

A key issue in QoS-provisioning real-time wireless communications is to provide the QoS requirement with low energy consumption. In this paper, we propose an energy-efficient error correction scheme for real-time communications with QoS requirements in wireless networks. The QoS requirement of a message stream is modeled with (m, k) constraint, implying that at least m messages should be sent to a receiver during any window of k periods. The proposed scheme adaptively selects an error correcting code in an energy-efficient manner so that it maximizes the number of QoS provisionings per unit energy consumption.

The RFID (Radio Frequency IDentification) tag technology is expected as a tool of localization. By the localization of RFID tags, a mobile robot which installs in RFID readers can recognize surrounding environments. In addition, RFID tags can be applied to a navigation system for walkers. In this paper, we propose an adaptive likelihood distribution scheme for the localization of RFID tags. This method adjusts the likelihood distribution depending on the signal intensity from RFID tags. We carry out the performance evaluation of estimated position error by both computer simulations and implemental experiments. We show that the proposed system is more effective than the conventional system.

Augmented reality tasks require a high-reliability tracking method. Large tracking error causes many problems during AR applications. Tracking error estimation should be integrated with them to improve the reliability of tracking methods. Although some tracking error estimation methods have been developed, they are not feasible to be integrated because of computational speed and accuracy. For this study, a tracking error estimation algorithm with screen error estimation based on the characteristic of linecode marker was applied. It can rapidly estimate tracking error. An evaluation experiment was conducted to compare the estimated tracking error and the actual measured tracking error. Results show that the algorithm is reliable and sufficiently fast to be used for real-time tracking error warning or tracking accuracy improvement methods.