This paper presents a technique to enhance in-band mismatch noise reduction of multi-stage second order Dynamic Element Matching (DEM) in multi-level ΔΣ Digital-to-Analog Converters (DACs). The presented technique changes an operational behavior of multi-stage DEM to reduce mismatch noise at in-band frequency. This change improves mismatch noise shaping performance for small amplitude input signals. Simulation result using 2-stage second order DEM and a third order 17-level ΔΣ modulator with 0.5% analog element mismatch shows 3.4 dB dynamic range improvement.

We propose a system that, using video information, segments the mouth region from a face image and then detects the protrusion of the tongue from inside the oral cavity. Initially, under the assumption that the mouth is closed, we detect both mouth corners. We use a set of specifically oriented Gabor filters for enhancing horizontal features corresponding to the shadow existing between the upper and lower lips. After applying the Hough line detector, the extremes of the line that was found are regarded as the mouth corners. Detection rate for mouth corner localization is 85.33%. These points are then input to a mouth appearance model which fits a mouth contour to the image. By segmenting its bounding box we obtain a mouth template. Next, considering the symmetric nature of the mouth, we divide the template into right and left halves. Thus, our system makes use of three templates. We track the mouth in the following frames using normalized correlation for mouth template matching. Changes happening in the mouth region are directly described by the correlation value, i.e., the appearance of the tongue in the surface of the mouth will cause a decrease in the correlation coefficient through time. These coefficients are used for detecting the tongue protrusion. The right and left tongue protrusion positions will be detected by analyzing similarity changes between the right and left half-mouth templates and the currently tracked ones. Detection rates under the default parameters of our system are 90.20% for the tongue protrusion regardless of the position, and 84.78% for the right and left tongue protrusion positions. Our results demonstrate the feasibility of real-time tongue protrusion detection in vision-based systems and motivates further investigating the usage of this new modality in human-computer communication.

This paper proposed a novel platform for sensor nodes to resolve the energy and latency challenges. It consists of a processor, an adaptive compressing module and several compression accelerators. We completed the proposed chip in a 0.18µm HJTC CMOS technology. Compared to the software-based solution, the hardware-assisted compression reduces over 98% energy and 212% latency. Besides, we balanced the energy and latency metric using an adaptive module. According to the scheduling algorithm, the module tunes the state of the compression accelerator, as well as the sampling frequency of the online sensor. For example, given a 9µs constraint for a 1-byte operation, it reduces 34% latency while the energy overheads are less than 5%.

We develop an effective algorithm, based on the filtered backprojection (FBP) approach, for the imaging of vegetation. Under the FBP scheme, the reconstruction amounts at a non-trivial Fourier inversion, since the data are Fourier samples arranged on a non-Cartesian grid. The computational issue is efficiently tackled by Non-Uniform Fast Fourier Transforms (NUFFTs), whose complexity grows asymptotically as that of a standard FFT. Furthermore, significant speed-ups, as compared to fast CPU implementations, are obtained by a parallel versions of the NUFFT algorithm, purposely designed to be run on Graphic Processing Units (GPUs) by using the CUDA language. The performance of the parallel algorithm has been assessed in comparison to a CPU-multicore accelerated, Matlab implementation of the same routine, to other CPU-multicore accelerated implementations based on standard FFT and employing linear, cubic, spline and sinc interpolations and to a different, parallel algorithm exploiting a parallel linear interpolation stage. The proposed approach has resulted the most computationally convenient. Furthermore, an indoor, polarimetric experimental setup is developed, capable to isolate and introduce, one at a time, different non-idealities of a real acquisition, as the sources (wind, rain) of temporal decorrelation. Experimental far-field polarimetric measurements on a thuja plicata (western redcedar) tree point out the performance of the set up algorithm, its robustness against data truncation and temporal decorrelation as well as the possibility of discriminating scatterers with different features within the investigated scene.

This paper studies the design of Cascade Granular Neural Networks (CGNN) for human-centric systems. In contrast to typical rule-based systems encountered in fuzzy modeling, the proposed method consists of two-phase development for CGNN. First, we construct a Granular Neural Network (GNN) which could be treated as a preliminary design. Next, all modeling discrepancies are compensated by a second GNN with a collection of rules that become attached to the regions of the input space where the error is localized. These granular networks are constructed by building a collection of user-centric information granules through Context-based Fuzzy c-Means (CFCM) clustering. Finally, the experimental results on two examples reveal that the proposed approach shows good performance in comparison with the previous works.

We address the stability property of the FAST TCP congestion control algorithm. Based on a continuous-time dynamic model of the FAST TCP network, we establish that FAST TCP in itself is globally exponentially stable without any specific conditions on the congestion control parameter or the update gain. Simulation results demonstrate the validity of the global exponential stability of FAST TCP.

In this paper, a frequency domain adaptive antenna array (FDAAA) algorithm is proposed for broadband single-carrier uplink transmissions in a cellular system. By employing AAA weight control in the frequency domain, the FDAAA receiver is able to suppress the multi-user interference (MUI) and the co-channel interference (CCI). In addition, the channel frequency selectivity can be exploited to suppress the inter-symbol interference (ISI) and to obtain frequency diversity (or the multi-path diversity). Another advantage of the FDAAA algorithm is that its performance is not affected by the spread of angles of arrival (AOA) of the received multi-path signal. In this study the structure of FDAAA receiver is discussed and the frequency domain signal-to-interference-plus-noise-ratio (SINR) after weight control is investigated. The performance of the FDAAA algorithm is confirmed by simulation results. It is shown that, the optimal FDAAA weight to obtain the best BER performance is that which fully cancels the interference when single-cell system is considered; On the other hand, when multi-cell cellular system is considered, the optimal FDAAA weight depends on both the cellular structure and the target signal to noise ratio (SNR) of transmit power control (TPC).

An ability to assess similarity lies close to the core of cognition. Its understanding support the comprehension of human success in tasks like problem solving, categorization, memory retrieval, inductive reasoning, etc, and this is the main reason that it is a common research topic. In this paper, we introduce the idea of semantic differences and commonalities between words to the similarity computation process. Five new semantic similarity metrics are obtained after applying this scheme to traditional WordNet-based measures. We also combine the node based similarity measures with a corpus-independent way of computing the information content. In an experimental evaluation of our approach on two standard word pairs datasets, four of the measures outperformed their classical version, while the other performed as well as their unmodified counterparts.

We describe a concept and realization of distance-adaptive (DA) resource allocation in spectrum-sliced elastic optical path network (SLICE). We modify the modulation format and cross-connection bandwidth of individual fixed-bit rate optical paths to optimize performance with respect to transmission distance. The shorter paths are allocated a smaller amount of resources which allows reducing the spectrum occupied by the channel. We show in calculation a reduction in required spectral resources of more than 60% when compared to the traditional traffic allocation schemes based on ITU-T grid. The concept is verified experimentally.

An algorithm for estimating sinusoidal parameters is presented. In this paper, it is assumed that an observed signal is a single sinusoidal signal contaminated by white Gaussian noise. Based on this assumption, the sinusoidal parameters can be found by minimizing a cost function using the mean squared error (MSE) between the observed signal and a sinusoidal signal with arbitrary sinusoidal parameters. Because the cost function is nonlinear and not convex, it has undesirable local minima. To solve the minimization problem, we propose to use the roots of an algebraic equation. The algebraic equation is derived straightforwardly from the cost function. We show that the global solution is formulated by using the roots of the algebraic equation.

This paper proposes a windowed-sinc function based peak-to-average power ratio (PAPR) reduction scheme for applying the polar transmitter techniques to orthogonal frequency division multiplexing (OFDM), where the high PAPR problem occurs. The proposed algorithm mitigates the effect of excessive suppression due to successive peaks or relatively high peaks of a signal, which is often observed when applying the conventional peak windowing scheme. The bit error rate (BER) and error vector magnitude (EVM) performances are measured for various window types and lengths. The simulation results demonstrate that the proposed algorithm achieves significant improvement in terms of BER and PAPR reduction performance while maintaining similar spectrum performance compared to the conventional peak windowing scheme.

In this paper, a novel receiver architecture is proposed for multiple-input-multiple-output (MIMO) systems; the proposed architecture helps achieve superior performance in multipath fading channels when the number of layered streams exceeds the number of receiving antennas. In this architecture, the concept of “virtual channel” is adopted to attain diversity gain even when successive detection is applied for reducing computational complexity, while orthogonal frequency division multiplexing (OFDM) is employed to combat multipath fading. Actually, successive detection is carried out in all possible virtual channels, and the virtual channel with the minimum error probability is detected with the assistance of the maximum a-posteriori (MAP) decoder in the architecture. In addition, soft input and soft output (SISO) iterative detection is introduced in the virtual channel estimation scheme. The performance of the proposed architecture is verified by computer simulations. This architecture can be implemented with lesser complexity than that in maximum likelihood detection (MLD), but the gain in the former case exceeds that in the latter by 4.5 dB at the BER of 10-3 for 42 MIMO-OFDM.

The present paper introduces a new approach to the construction of a sequence set with a zero-correlation zone for both periodic and aperiodic correlation functions. The proposed sequences can be constructed from a pair of Hadamard matrices of orders n0 and n1. The constructed sequence set consists of n0 n1 ternary sequences, each of length n0(m+2)(n1+Δ), for a non-negative integer m and Δ ≥ 2. The zero-correlation zone of the proposed sequences is |τ| ≤ n0m+1-1, where τ is the phase shift. The proposed sequence set consists of n0 subsets, each with a member size n1. The correlation function of the sequences of a pair of different subsets, referred to as the inter-subset correlation function, has a zero-correlation zone with a width that is approximately Δ times that of the correlation function of sequences of the same subset (intra-subset correlation function). The inter-subset zero-correlation zone of the proposed sequences is |τ| ≤ Δn0m+1, where τ is the phase shift. The wide inter-subset zero-correlation enables performance improvement during application of the proposed sequence set.

The design of an energy-efficient wavelength division multiplexing (WDM) transponder is proposed and effectiveness of the proposed WDM transponder is experimentally studied. The proposed WDM transponder interworking with the link-aggregation technique possessed by a layer 2 switch can achieve power saving depending on traffic volume variations by utilizing an adaptive interface control. Monitoring methods for the link connectivity of a sleep link are also discussed.

High-performance 1.3-µm electroabsorption modulators integrated with DFB lasers are developed for long-reach 100 Gbit Ethernet. The dynamic extinction ratio of over 8-dB with the voltage swing of 2 V are achieved for the four LAN-WDM lanes (14 nm wavelength range) used in 100 Gbit Ethernet with the same modulator structure. The fabricated devices are packaged in butterfly modules and four-lane 40-km single mode fiber transmission at 25-Gbit/s operation is demonstrated. Further, a can-type transmitter optical subassembly is fabricated to reduce the cost and size of transmitter modules. The use of a low-dielectric-constant liquid crystal polymer transmission line makes the 3-dB bandwidth larger and enables 25-Gbit/s operation with CAN-TOSA module.

We demonstrate an all-optical picosecond pulse duration-tunable nonreturn-to-zero (NRZ)-to-return-to-zero (RZ) data format conversion using a Raman amplifier-based compressor and a fiber-based four-wave mixing (FWM) switch. A NRZ data signal is injected into the fiber-based FWM switch (AND gate) with a compressed RZ clock by the Raman amplifier-based compressor, and convert to RZ data signal by the fiber-based FWM switch. The compressed RZ clock train acts as a pump signal in the fiber-based FWM switch to perform the NRZ-to-RZ data format conversion. By changing the Raman pump power of the Raman amplifier-based compressor, it is possible to tune the pulse duration of the converted RZ data signal from 15 ps to 2 ps. In all the tuning range, the receiver sensitivity at bit error rate (BER) of 10-9 for the converted RZ data signal was about 1.31.7 dB better than the receiver sensitivity of the input NRZ data signal. Moreover, the pulse pedestal of the converted RZ data signals is well suppressed owing to the FWM process in the fiber-based FWM switch.

Nearest neighbor search (NNS) among large-scale and high-dimensional vectors plays an important role in recent large-scale multimedia search applications. This paper proposes an optimized multiple codebook construction method for an approximate NNS scheme based on product quantization, where sets of residual sub-vectors are clustered according to their distribution and the codebooks for product quantization are constructed from these clusters. Our approach enables us to adaptively select the number of codebooks to be used by trading between the search accuracy and the amount of memory available.

Existing filtering methods of TCP ACK packets are known to be effective in reducing the required bandwidth, resulting in the improvement of TCP throughput. However, the methods cannot handle the filtering of piggyback ACK packets. Considering that most TCP applications require bidirectional data exchange, the lack of the functionality to deal with the piggyback ACK packets should be addressed. This paper proposes a novel filtering scheme for WiMAX systems that can handle the piggyback ACK packets. The novelty comes from the fact that the proposed method overlaps the processing time of packet merging with the round trip delay of the bandwidth request-and-grant procedure. It is advantageous because it does not require extra time for the merging. The results from an analytical model and simulations show that the required uplink bandwidth is decreased while the downlink throughput is increased.

A stereo video coding scheme which is compatible with monoview-processor is presented in this paper. At the same time, this paper proposes an adaptive prediction structure which can make different prediction modes to be applied to different groups of picture (GOPs) according to temporal correlations and interview correlations to improve the coding efficiency. Moreover, the most advanced video coding standard H.264 is used conveniently for maximize the coding efficiency in this paper. Finally, the effectiveness of the proposed scheme is verified by extensive experimental results.

A novel signaling scheme is proposed for iterative channel estimation and data decoding in fast fading channels. The basic idea is to bias the occurrence probability of transmitted symbols. A priori information about the bias is utilized for channel estimation. The bias-based scheme is constructed as a serially concatenated code, in which a convolutional code and a biased nonlinear block code are used as the outer and inner codes, respectively. This construction allows the receiver to estimate channel state information (CSI) efficiently. The proposed scheme is numerically shown to outperform conventional pilot-based schemes in terms of spectral efficiency for moderately fast fading channels.