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In a paper industry, especially in thick stock wet end process, the two most important variables are retention in forming section of a paper machine and basis weight of the thick stock. Present paper attempts to understand the governing mass balance equations which may be required to deduce an appropriate process model.

We study the problem of transmitting a message over a channel that randomly breaks the message block into small fragments, deletes a subset of them, and shuffles the remaining fragments. We characterize the capacity of the binary torn-paper channel under arbitrary fragment length distribution and fragment deletion probabilities. We show that, for a message with block length $n$ , discarding fragments shorter than $\log(n)$ does not affect the achievable rates, and that the capacity is given by a simple closed-form expression that can be understood as “coverage minus reordering-cost”.

The condition of the transformer insulation has an impact on the transformer’s performance during the operation. The aging of the oil-impregnated cellulose insulation and the associated loss of mechanical strength are the important factors that limit the life of expectancy of a transformer. To determine the condition of the oil-impregnated cellulose insulation, the Degree of Polymerization (DP) parameter is commonly used. An Adaptive Neuro-Fuzzy Inference System (ANFIS) has been developed to predict the DP Value by the chemical characteristics and dissolved gas parameters (acidity, interfacial tension, CO, CO 2 , breakdown voltage, and water content of the oil). This paper generates some algorithms which are based on the input space partitioning method to generate rules (grid partition or subtractive clustering) and data is normalized or not. The estimation result has been observed and evaluated to provide that the ANFIS algorithm is suitable to estimate insulation condition on field operating transformers.

Oil paper insulation is the main insulation form of large transformers. Partial discharge(PD) in oil paper insulation will not only damage the insulation performance, but also is the precursor and manifestation of insulation deterioration. Weibull distribution parameter is an important characteristic parameter of PD. In this paper a method is proposed to extract the characteristic parameter of PD based on the three-parameter Weibull model, then gray wolf optimization algorithm and particle swarm optimization algorithm are used to calculate the parameters of the model. The result shows that the two algorithms can get the parameters quickly and accurately, and the model can effectively reflect the characteristics of the $H_{n}(q)$ spectrum of PD times.

This paper deals with the observer design of nonlinear tubular chemical reactor models. The analysis is performed on a linearized version of the model around a steady-state profile, in which some coefficients are a function of the spatial variable. The study starts from a general model of chemical tubular reactors that will serve as a benchmark model for the formulation in the infinite dimensional Hilbert state space. The optimal output injection operator associated to the proposed observer is computed via the solution of the infinite-dimensional Riccati equation in the space variable. The performance of the observer is illustrated through numerical experiments of an industrial pulp bleaching tubular reactor model.

A modified version of Costa's dirty paper channel is studied, in which both the input signal and the state experience stationary and ergodic time-varying fading. The fading coefficients are assumed to be known exclusively at the receiver. An inner bound of the achievable rates using lattice codes is derived and compared to an outer bound of the capacity. For a wide range of fading distributions, the gap to capacity is within a constant value that does not depend on either the power of the input signal or the state. The results presented in this paper are applied to a class of ergodic fading broadcast channels with receive channel state information, where the achievable rate region is shown to be close to capacity under certain configurations.

Print image processing is largely based on the paper whiteness, which is a matter that still has no precise definition. Different international standards determine whiteness diversely. Paper composition, obviously, affects the whiteness, however, few is known about the influence on whiteness that produces particular chemical element in paper. This paper aims to establish the relationship between paper whiteness and the content. We describe an approach to paper whiteness assessment taking into account the filler elements content. We distinguish 255 sample papers by their color difference dE94 in comparison with the standard paper that has CIE Lab coordinates (95/0/-2). The X-ray fluorescence analysis reveal 25 chemical elements in paper samples. Based on that, the clustering of papers and further discriminant analysis reveal four clusters with distinguishable paper composition and whiteness. We figure out 12 elements that show the most influence on the paper whiteness (S, Ti, Mn, Zn, Rb, Sr, Y, Zr, Sb, I, Ba, Th).

Consider a two-user MIMO Gaussian Broadcast Channel with two antennas at the transmitter and two single-antenna receivers. While Dirty Paper Coding (DPC) achieves capacity, its practical adoption needs a precise comparison with the popular method of Zero Forcing Beam Forming (ZFBF). In this work, we obtain a simplified expression for the exact difference in sum rate between DPC and ZFBF at all SNRs. Using this expression, we obtain the distribution of the difference under block fading, and show a significant improvement in rate in wideband OFDM transmission by using DPC for only a small fraction of subcarriers.

In wireless communication, Multi-Input Multi-Output (MIMO) technology offers significant increase in data throughput and link range without additional bandwidth. The dirty paper coding (DPC) achieves the sum rate capacity of Gaussian MIMO broadcast channel. The dirty paper coding is a technique for efficient transmission of digital data through a channel that is subject to some interference that is known to the transmitter. This technique consists of precoding the data so as to cancel the effect of interference. The duality relationship between BC and MAC channel has been studied and The Sato upper bound and Marton's inner bound on the capacity of Broadcast channel has been considered and applied this capacity to the MAC channel by showing the duality. The use of dirty paper coding closely achieves the sum-rate capacity region of broadcast channel. MIMO is abbreviation of Multiple Input Multiple Output. In MIMO fading environment, the so called degenerating channels or keyholes may exist that exhibit low partial fading correlation at both ends of the link but still have poor rank properties, and hence low ergodic capacity. The performance of dirty-paper coding over MIMO keyhole channels has been analyzed. The capacity and the probability of error of a MIMO system with Binary phase shift keying (BPSK) over keyhole channel. This paper also proves the intuitive result that the capacity under keyhole condition can be improved using Dirty paper coding.

Pass researches on STEM education emphasized the rational problem solving among applied engineering and technology, while the nurture of the imagination and creativity in the students’ art field was overlooked. Hence, this research aims to develop a STEAM curriculum module, with basic electronic technology and skill as the foundation, combining scientific RGB colour theory and the artistic concept of drawing and modelling design, with application of the Adobe Illustrator and SketchUp softwares, developing into a hands-on module "LED light-adjusting and paper-curved pop up card" STEAM curriculum. This research combined expert teachers from electrical engineering, physics and art fields to collaboratively develop the curriculum module, through reflective dialogues of three instructing teachers and two team teachers, experiencing three years of curriculum module revision. The first year developed the integrated curriculum of the mini DIY LED light-adjusting board that combined technology, engineering and mathematics, the second year combined with science concept and developed the STEM curriculum for LED light-adjusting board experiments, the third year combined with the artistic paper-curved pop up card and developed the STEAM curriculum module. This module can be applied in the living technology curriculum of the grade 8, which based on student-centred learning, with application of 6E Learning by DeSIGN™ Model for teaching, and this STEAM curriculum module can provide and be applied in 24 lessons of the secondary school’s living technology curriculum.

In this paper, a practical multiple input multiple output Dirty paper coding (MIMO-DPC) scheme is designed to cancel the effect of additive interference that is known perfectly to the transmitter. The proposed system uses a trio of encoders — a LDPC code, a vector quantizer implemented as a convolutional decoder and an Orthogonal space time block code (STBC) to achieve temporal coding gain, interference cancelation and spatial diversity, respectively. First, we derive the equivalent noise seen by the receiver using an equivalent lattice based dirty paper code. Then the optimal value of the power inflation factor, which is one of the key system parameters used to minimize the equivalent noise seen by the receiver is derived. Furthermore, we analytically prove that the equivalent noise seen by the receiver tends to 0 for large number of receive antennas. Performance results in the case of various number of receiver antennas are presented and show that significant reduction in bit error probabilities can be obtained over a system that uses no interference cancelation.

Savonius rotor is a very popular vertical shaft power generation impeller, with the advantage of small starting torque and low cost. In order to improve the maximum power coefficient of the impeller, this paper presents a method using B spline optimization to get the best solution. The new design of the blades' shape is controlled by three variable points and two threefold fixed points. With the decrease of vertical height, the best power coefficient shows the trend of increasing first and then decreasing. With the increase of the horizontal offset, the optimal power coefficient shows a tendency of increasing first and then decreasing. By comparing all simulation data, the case H1 is the best blade curve. Its maximum power coefficient of 0.288 is 3.2% greater than the original blade.

The capacity region of the Gaussian interference channel with two source-destination pairs where the sources can cooperate is not known. Prabhakaran and Viswanath showed that the sum-rate capacity can be achieved to within 19 bits/s/Hz by using a combination of superposition coding and zero-forcing. This paper only focuses on the symmetric capacity, i.e., the maximum equal rate point that the two sources can simultaneously achieve in a Gaussian interference channel with symmetric channel gains, in the strong cooperation regime, i.e., when the cooperation link is stronger than either the direct link or the interference link. In this setting, it is showed that the “binning+superposition” achievable scheme of Yang and Tuninetti, implemented with Gaussian codebooks and Dirty Paper Coding, achieves the symmetric capacity to within 2 bits/s/Hz-thereby considerably reducing the previously known gap. The extension of this gap-result to other regimes is also discussed.

We consider the beamformer design for zero-forcing dirty paper coding (ZF-DPC), a suboptimal transmission technique for MISO broadcast channels (MISO BCs). For the sum rate maximization problem under a total power constraint, the existing beamformer designs in the literature are based on the QR decomposition (QRD), which is used to satisfy the ZF constraints. However, the optimality of the QRD-based design has been unknown previously. In this paper, we prove that the QRD-based design is optimal for ZF-DPC for any performance measure under a sum power constraint. For the per-antenna power constraints, the QRD-based designs become suboptimal, and we propose an optimal design, using a convex optimization framework. Low-complexity suboptimal designs are also presented, and numerically shown to achieve a significant fraction of the sum rate provided by the optimal design.

This paper focuses on the signal processing algorithm for the downlink of Multi-User Multiple-Input Multiple-Output (MU-MIMO). In this paper, a novel transmission scheme is proposed for the cancellation of IUI (Inter-User Interference) in MU-MIMO downlinks. Compared with the conventional DPC with single receive antenna, the users in the proposed scheme are equipped with multiple receive antennas, even though the principle of the DPC (Dirty Paper Coding) in MU-MIMO is the same. For the users with multiple receive antennas, the maximum eigenvectors for all user channels are calculated first and then we select the user with the maximum eigenvector as the 1-st user. For the remaining users, the transmit weights are generated from the weights of previous selected users by using the algorithm which makes the each user gain as large as possible. We also use the DPC principle to cancel the IUI at the base station. Through computer simulations, we have shown that the proposed scheme achieves an excellent BER characteristic compared with the conventional DPC, especially when multiple receive antennas are used for each user.

This paper studies dirty-paper coding in a Gaussian broadcast channel with two receivers. It finds that an approximate version of dirty-paper coding using low-density lattices can be implemented with a complexity that is polynomial-time on average in the block length. The main difference between this paper and prior work is that a non-binary LDPC-based lattice codebook is used for each user, and one codebook is aligned with the other. The low-density nature enables tractable encoding and decoding algorithms, and the alignment gives structure to the overall signal transmitted and it enables us to perform the encoding and decoding efficiently.1

Dirty paper coding scheme (DPC) is known to be a capacity achieving transmission technique in downlink multiuser MIMO channels. As a suboptimal solution to DPC, a precoding technique called successive zero-forcing dirty paper coding (SZF-DPC) has been proposed recently. The condition for the existence of the precoding matrices in SZF-DPC restricts the capability of supporting multiple users simultaneously. Thus, a user scheduling algorithm is needed to achieve multiuser diversity in SZF-DPC as the number of users grows. In this paper, we propose three low-complexity suboptimal scheduling algorithms to exploit the multi-user diversity gain for SZF-DPC. The first algorithm greedily maximizes the true sum capacity. The second algorithm is based on eigenvalues that are closely related to the true capacity. The third algorithm relies on the diagonal elements of the effective channel matrix since we realize a strong relationship between the eigenvalues and diagonal entries of a Hermitian matrix. Simulation results of several cases show that the proposed scheduling algorithms can obtain a significant fraction of sum capacity of the optimal solution.

The vector dirty paper coding (DPC) can achieve rate region for multicell cooperation system. Conventional DPC implementation approach suffer the capacity loss due to quantization which lead to modulo loss. In this paper, we proposed a vector DPC transmission scheme with non-binary LDPC codes and low density generator matrix based quantizer for multicell processing. And the random coding based proof for the encoding and decoding transmission system is presented. It can achieve a shaping gain and significantly reduce computational complexity.

The problem of dirty paper coding (DPC) over the (multi-antenna) fading dirty paper channel (FDPC) Y = H(X + S) + Z is considered when there is imperfect knowledge of the channel state information H at the transmitter (CSIT). The case of FDPC with positive definite (p.d.) input covariance matrix was studied by the authors in a recent paper, and here the more general case of positive semi-definite (p.s.d.) input covariance is dealt with. Towards this end, the choice of auxiliary random variable is modified. The algorithms for determination of inflation factor proposed in the p.d. case are then generalized to the case of p.s.d. input covariance. Subsequently, the largest DPC-achievable high-SNR (signal-to-noise ratio) scaling factor over the no-CSIT FDPC with p.s.d. input covariance matrix is derived. This scaling factor is seen to be a non-trivial generalization of the one achieved for the p.d. case. Next, in the limit of low SNR, it is proved that the choice of all-zero inflation factor (thus treating interference as noise) is optimal in the 'ratio' sense, regardless of the covariance matrix used. Further, in the p.d. covariance case, the inflation factor optimal at high SNR is obtained when the number of transmit antennas is greater than the number of receive antennas, with the other case having been already considered in the earlier paper. Finally, the problem of joint optimization of the input covariance matrix and the inflation factor is dealt with, and an iterative numerical algorithm is developed., Presented at the 43rd Annual Conference on Information Sciences and Systems, John Hopkins University, March 2009

Existing dirty-paper coding (DPC) schemes based on binned FEC codes lack of tractable BER analysis, hence it is difficult to predict the performance behavior of DPC. In this paper, we derive closed-form BER upper bounds of binned Walsh-Hadamard codes and binned Gold codes as DPC. Their BER upper bounds are verified to be very tight under the condition that the channel contains side information only, or side information plus noise.

In this paper, an effort has been made to explore the usefulness of DP (Degree of Polymerization) of cellulosic insulation paper (CIP) to monitor the condition of the transformer. The residual life of CIP of the oil-immerged power transformer is determined by detecting the content of dissolved carbon oxide and 2-FAL gases in oil. The proposed work employs Fuzzy Inference System (FIS), which offers preeminent response for calculating extent of degradation of the CIP. Using the FIS the final condition of CIP is categorized as AI (Acceptable Insulation), MD (Moderate Deterioration), ED (Extensive Deterioration) and UR (Urgent Replacement) from correlation between accumulated values of 2-FAL, CO and CO2 with DP. Furthermore, the best fuzzy membership function has been obtained for the experimental test condition. Finally the results obtained shows that the proposed method accurately monitors the condition of CIP in the oil-immerged power transformers.

This paper presents the possibility of using Adaptive Neuro Fuzzy Inference System for Power Transformer Paper Condition Assessment. The dielectric characteristics, dissolved gasses, and furan of 108 running transformers is collected. The 2-furaldehyde (2FAL) data is transformed to Degree of Polymerization (DP), and then statistically analysed to get independent variables as the predictor for the transformer paper condition assessment. CO and CO2 are well known as one of the product of cellulose degradation, while interfacial tension, acidity, and color from the oil are statistically correlated with furan. ANFIS (Adaptive Neuro-Fuzzy Inference System) and Multiple Regression (MR) model is built based on the previous statistical analysis, and then the result is evaluated and compared, resulting in better accuracy of ANFIS model. Three different evaluation criteria MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error), and RMSE (Root Mean Square Error) calculated from ANFIS prediction are lower than those from MR model, with the MAPE of ANFIS model is 15.38%.

This paper proposes a method of searching for promising young researchers using network centrality of co-author relationship. This method estimates researchers' potential based on transition of betweenness centralities in co-author networks. We thought that excellent researchers always show high betweenness centralities, in contrast, betweenness centralities of promising researchers will grow with time. As a result of network analysis, we detected some researchers with growing betweenness centralities from the academic paper database of Japan Science and Technology Agency (JST). In addition, Japan Society for the Promotion of Science (JSPS) Research Fellows who had been evaluated as a promising young researcher by JSPS showed growing betweenness centralities. Therefore, our proposed method is useful to search for promising young researchers in collaborative research fields such as biological science.

Dirty paper coding (DPC) refers to methods for pre-subtraction of known interference at the transmitter of a multiuser communication system. There are numerous applications for DPC, including coding for broadcast channels. Recently, lattice-based coding techniques have provided several designs for DPC. In lattice-based DPC, there are two codes - a convolutional code that defines a lattice used for shaping and an error correction code used for channel coding. Several specific designs have been reported in the recent literature using convolutional and graph-based codes for capacity-approaching shaping and coding gains. In most of the reported designs, either the encoder works on a joint trellis of shaping and channel codes or the decoder requires iterations between the shaping and channel decoders. This results in high complexity of implementation. In this work, we present a lattice-based DPC scheme that provides good shaping and coding gains with moderate complexity at both the encoder and the decoder. We use a convolutional code for sign-bit shaping, and a low-density parity check (LDPC) code for channel coding. The crucial idea is the introduction of a one-codeword delay and careful parsing of the bits at the transmitter, which enable an LDPC decoder to be run first at the receiver. This provides gains without the need for iterations between the shaping and channel decoders. Simulation results confirm that at high rates the proposed DPC method performs close to capacity with moderate complexity. As an application of the proposed DPC method, we show a design for superposition coding that provides rates better than time-sharing over a Gaussian broadcast channel., 5 pages, submitted to ISIT 2010

A bound on the capacity of the causal dirty paper problem with arbitrary interference and general independent identically distributed additive noise is derived. In particular, it is shown that for the case of Gaussian noise the capacity is upper bounded by log 2 (1 + SNR over e) bits per real dimension. This bound is useful for SNR ≤ e(e - 2).

Dirty paper coding (DPC) is a promising preceding technique for canceling arbitrary interference known only at the transmitter. The interference-free rate is thus achieved. However, this result relies on the perfectly known channel coefficients at the transmitter when being applied to the fading channel. We thus consider the fading paper problem where only the channel statistics information is available at the transmitter. In general, the optimal transmission strategies to achieve the capacity of this channel is still unknown. We confine ourselves to the linear-assignment Gel'fand-Pinsker coding which has been proved to have good, sometimes even optimal, performance in the a variety of fast and slow fading channels. However, lack of structured codebook so far limited the practical applications of this coding. In this paper, we present a lattice-based coding structure for the vector fading paper channel. It can achieve the rate performance of the linear-assignment strategies previously proved by the random Gaussian codebook. Moreover, the lattice codebook has an algebraic structure and is possible to be implemented in practice. The results can be applied to the emerging fields such as fading multiple-input multiple-output (MIMO) Gaussian broadcast channels or fading MIMO cognitive channels.

We design a coding scheme for Costa's dirty paper coding (DPC) (M.H.M. Costa, 1983) using a channel and a shaping code. We show that by transforming the channel noise distribution the DPC channel can be converted into the binary erasure channel (BEC) with binary interference with memory. Furthermore, the messages exchanged during the iterative decoding between the channel and shaping codes become one dimensional under the new model. We analyze the iterative decoding and find good shaping and channel code pairs using some closed-form extrinsic information transfer (EXIT) curves. We verify that our dirty paper codes designed using this method are also good for the original DPC channel with the additive white Gaussian noise (AWGN) and arbitrary interference. Our implementation of DPC uses short block codes such as repetition codes for shaping codes. Although the shaping gains of such codes are not very high, they may provide a better complexity-performance trade-off for simple practical implementations of DPC. Furthermore, we show accurate theoretical analysis is possible for such codes under our channel model.

A Dirty Paper Coding (DPC) based transmission scheme for the Gaussian multiple-input multiple-output (MIMO) cognitive radio channel (CRC) is studied when there is imperfect and perfect channel knowledge at the transmitters (CSIT) and the receivers, respectively. In particular, the problem of optimizing the sum-rate of the MIMO CRC over the transmit covariance matrices is dealt with. Such an optimization, under the DPC-based transmission strategy, needs to be performed jointly with an optimization over the inflation factor. To this end, first the problem of determination of inflation factor over the MIMO channel $Y=H_1 X + H_2 S + Z$ with imperfect CSIT is investigated. For this problem, two iterative algorithms, which generalize the corresponding algorithms proposed for the channel $Y=H(X+S)+Z$, are developed. Later, the necessary conditions for maximizing the sum-rate of the MIMO CRC over the transmit covariances for a given choice of inflation factor are derived. Using these necessary conditions and the algorithms for the determination of the inflation factor, an iterative, numerical algorithm for the joint optimization is proposed. Some interesting observations are made from the numerical results obtained from the algorithm. Furthermore, the high-SNR sum-rate scaling factor achievable over the CRC with imperfect CSIT is obtained., To be presented at ISIT 2009, Seoul, S. Korea

We study a dirty paper channel model where the input is constrained to belong to a PAM constellation. In particular, we provide lower bounds on the capacity as well as explicit coding schemes for the binary-input dirty-paper channel. We examine the case of causal as well as non-causal side information.

We consider the MIMO broadcast channel where a base station with multiple antennas transmits simultaneously to many users. The optimum strategy with Channel State Information (CSI) at the transmitter is based on Dirty Paper Coding (DPC) principles. In this paper, we propose a suboptimum strategy suitable when terminals are equipped with multiple antennas. This approach combines DPC and receive beam-forming and is shown to provide near-optimum performance with very reasonable complexity. Beamforming design is based on the maximization of the sum rate while precoder design is based on Zero Forcing (ZF) criteria. We have to remark that it is not required iterative processes or interaction between transmitter and receivers to find the suboptimum solution. It is also important to mention that each terminal just needs to know its own channel to perform the optimization while the base station requires full knowledge of all users' channels.

In this paper, we improve the peak to average power ratio (PAPR) reduction scheme for multicarrier systems proposed by Collings and Clarkson by applying dirty paper coding with peak power constraint. We compare the bit error rate (BER) performance among conventional orthogonal frequency division multiplexing (OFDM), Collings and Clarkson’s method, and our proposed scheme with bit loading. From simulation we find that when channel coding is considered, Collings and Clarkson’s method is the worst independent of the number of bits loaded. The proposed method performs the best when the number of bits is large and hence is suitable for high speed transmission.

The Tomlinson-Harashima precoding is well known for dirty paper coding implementation. Despite its simplicity, THP suffers from a significant performance loss in the low SNR region due to modulo operations. In this paper, we propose new dirty paper precoding scheme by taking advantage of the known modulation structure of interference (e.g., BPSK and QPSK signals). The new method, termed structured DPC (SDPC), outperforms the regular THP with modest changes to the transmitter and receiver. For BPSK and QPSK cases investigated, the SDPC only suffers power loss, which is up to 1.25 dB compared with non-interference case, while the regular THP-based scalar dirty paper coding has a typical 4-5 dB capacity loss in the same low SNR regions

A dirty paper channel is considered, where the transmitter knows the interference sequence up to a constant multiplicative factor, known only to the receiver. We derive lower bounds on the achievable rate of communication by proposing a coding scheme that partially compensates for the imprecise channel knowledge.We focus on a communication scenario where the Gaussian noise is small while the interference is strong. Our approach is based on analyzing the performance achievable using extended Tomlinson-Harashima like coding schemes. When the power of the interference is finite, we show that this may be achieved by a judicious choice of the scaling parameter at the receiver. We further show that the communication rate may be improved, for finite as well as infinite interference power, by allowing randomized scaling at the transmitter.

This paper addresses near-capacity dirty-paper code designs based on TCQ and IRA codes, where the former is employed as the most efficient means of vector quantization and the latter for their capacity-approaching performance. By bringing together TCQ - the best quantizer from the source coding community and EXIT chart based IRA code designs - the best from the channel coding community, we are able to approach the theoretical limit of dirty-paper coding. For example, at 0.25 b/s, one of our code designs (with 1024-state TCQ) performs 0.83 dB away from the capacity

We present practical codes designed for the Gaussian dirty paper channel. We show that the dirty paper decoding problem can be transformed into an equivalent multiple-access problem, for which we apply superposition coding. Our approach is a generalization of the nested lattices approach of Zamir et al. (2002). We present simulation results which confirm the effectiveness of our methods.

The optimal controller design for spatially distributed dynamical systems is greatly simplified when spatially invariant models are used. However, the true spatial boundary conditions of many practical systems, including paper machine cross-directional processes, disrupt the spatial invariance and potentially destabilize the control system if not taken into account. This paper considers the design of stability preserving spatial boundary conditions for paper machine cross-directional controllers originally computed for idealized spatially invariant processes.

This paper describes a way of implementing DPC in a Gaussian MIMO broadcast channel. The outer encoder is based on a vector TCQ designed to possess certain "good properties". Simpler schemes such as the Tomlinson Harashima or Scalar Costa's scheme are also considered by a way of comparison. The inner encoder is implemented through a vector version of the ZF-DPC and the MMSE-DPC. The BER performance of the DPC schemes is evaluated and compared to that of conventional interference cancellers (pre-ZF, pre-MMSE). From simulation results the choices of the inner encoder, the outer encoder (THS/SCS/TCQ) and the interference cancellation technique (conventional or DPC) are discussed.

This paper presents a control strategy for regulating cross-directional basis weight variations on a paper machine. The control strategy is based upon minimising the expected range of the variations observed within a single scan across the width of the sheet. This can be considered as a l/sub /spl infin// minimisation problem which can be implemented using efficient algorithms based upon the simplex method of linear programming. The BIBO stability of the controlled system is analysed and it is shown that the stability of the full multivariable system is determined by the location of the zeros of a scalar dynamic term.

A modified paper clock timescale weighted after removing the linearized frequency drift of each cesium clock in TL's 12-cesium-clock ensemble is used to be the mid-term prediction reference before the next coming BIPM Circular T announcement. After removing the frequency drift pattern according to Circular T announcements, the noise type of each cesium clock in ensemble is dominated by white noise when the average time was less than about 100 days. To achieve approximately equal weighting and rational upper limit, an inversely exponential weighting procedure is also used to weight each cesium clock according to the inversely exponential function of their Allan variance; for our 12-cesium-clock ensemble, a 4 years test shows the phase error of the paper clock time scale is less than 10 ns in 45 days prediction.

Consider a Gaussian multiple-input multiple-output (MIMO) multiple-access channel (MAC) with channel matrix H and a Gaussian MIMO broadcast channel (BC) with channel matrix H⊺. For the MIMO MAC, the integer-forcing architecture consists of first decoding integer-linear combinations of the transmitted codewords, which are then solved for the original messages. For the MIMO BC, the integer-forcing architecture consists of pre-inverting the integer-linear combinations at the transmitter so that each receiver can obtain its desired codeword by decoding an integer-linear combination. In both cases, integer-forcing offers higher achievable rates than zero-forcing. In recent work, we established an uplink-downlink duality relationship for integer-forcing, i.e., we showed that any rate tuple that is achievable via integer-forcing on the MIMO MAC can be achieved via integer-forcing on the MIMO BC with the same sum power and vice versa. It has also been shown that integer-forcing for the MIMO MAC can be enhanced via successive cancellation. Here, we introduce dirty-paper integer-forcing for the MIMO BC and establish uplink-downlink duality with successive integer-forcing for the MIMO MAC.

In this paper, we study error in wave digital filter nonlinearities from an energetic perspective. By ensuring that power dissipation corresponding to this error is non-negative, we respect the basic wave digital filter premise that errors should not correspond to an increase in system energy. In particular, this has implications for the formation of lookup tables and the choice of lookup table interpolation method. We give recommendations for both based on the sign and second derivative of the wave-domain function which is to be tabulated. These recommendations are used to study interpolation of a diode characteristic.

Costa's “writing on dirty paper” result establishes that full state pre-cancellation can be attained in the Gel'fand-Pinsker problem with additive state and additive white Gaussian noise. This result holds under the assumptions that full channel knowledge is available at both the transmitter and the receiver. In this work we consider the scenario in which the state is multiplied by an ergodic fading process which is not known at the encoder. We study both the case in which the receiver has knowledge of the fading and the case in which it does not: for both models we derive inner and outer bounds to capacity and determine the distance between the two bounds when possible. For the channel without fading knowledge at either the transmitter or the receiver, the gap between inner and outer bounds is finite for a class of fading distributions which includes a number of canonical fading models. In the capacity approaching strategy for this class, the transmitter performs Costa's pre-coding against the mean value of the fading times the state while the receiver treats the remaining signal as noise. For the case in which only the receiver has knowledge of the fading, we determine a finite gap between inner and outer bounds for two classes of discrete fading distribution. The first class of distributions is the one in which there exists a probability mass larger than one half while the second class is the one in which the fading is uniformly distributed over values that are exponentially spaced apart. Unfortunately, the capacity in the case of a continuous fading distribution remains very hard to characterize.

This paper deals with the effect of the temperature on the partition of the furanic derivatives between the oil and paper insulation in power transformers. For the five chemical markers studied, due to its highest polarity, the 2-furfurol showed the highest difference compared to the other furanic species. The author's propose correction equations at 20°C for the normalization of the temperature for the furanic derivatives. These correction factors allow following the real trend of the markers during all the transformer life.

The research in this paper focuses on a state estimation problem for paper path and heat flow control of industrial printers. The nonlinear dynamics can be approximated, up to an arbitrary accuracy, with a piecewise linear system, and an arbitrary time driven switching law. The stability and performance of the estimators are analyzed and proven based on Lyapunov theory. Simulation examples show the effectiveness of the proposed approaches in the presence of several switches between modes.

Stripes are important features for scrap paper images mosaics. The stripe feature extraction can directly affect the effect of mosaics. A method of stripe feature extraction from scrap paper images is proposed in this paper. In order to obtain the background binary image, the original scrap paper images are firstly carried out by close operation and binarization. Secondly, the single pixel edges are extracted by using edge detection operator. Finally, the crossing points of stripes and the boundary of the background are detected by using the Progressive Probabilistic Hough Transformation. The length, angle and direction features of stripes are also extracted during this process. The experimental results show that the method of stripe feature extraction proposed in this paper is reasonable. By using this method the stripe features can be extracted from scrap paper images quickly and correctly. It provides features for the subsequent image mosaics.

To protect against modeling limitations in considering design and electrical complexities, as well as variability, early and late signal propagation times in static timing analysis are often made pessimistic by addition of extra guard bands. However, these forced early-late splits introduce excessive and undesired pessimism. To this end, common path pessimism removal (CPPR) eliminates guaranteed redundant pessimism during timing analysis. This session aims to highlight the importance of CPPR during timing analysis, as well as explore novel methods for fast CPPR from the top performers of the TAU 2014 timing contest.

Binned orthogonal/bi-orthogonal codes have been proposed as dirty-paper codes for digital watermarking due to its simplicity in both encoding and decoding, robustness against volumetric scaling, and performance gain over conventional non-dirty paper coded systems. In this paper, we extend the binned orthogonal/bi-orthogonal code to generalized binned linear binary code, and propose an efficient binning method to achieve good coding performance. We also derive a closed-form expression for its BER performance in dirty paper watermarking systems. Simulations show that the derived BER formula is very tight. The binned linear binary codes offer much higher code rates, hence significant coding gains, over its orthogonal/bi-orthogonal counterparts. This translates into improved invisibility for the hidden data and better perceptual quality for the watermarked image for a given robustness requirement for the hidden data.