With exponentially increasing power densities due to technology scaling and ever increasing demand for performance, chip temperature has become an important issue that limits the performance of computer systems. Typically, it is essential to use a set of on-chip thermal sensors to monitor temperatures during the runtime. The runtime thermal measurements are then employed by dynamic thermal management techniques to manage chip performance appropriately. In this paper, we propose an inverse distance weighting method based on a dynamic Voronoi diagram for the reconstruction of full thermal characterization of integrated circuits with non-uniform thermal sensor placements. Firstly we utilize the proposed method to transform the non-uniformly spaced samples to virtual uniformly spaced data. Then we apply three classical interpolation algorithms to reconstruct the full thermal signals in the uniformly spaced samples mode. To evaluate the effectiveness of our method, we develop an experiment for reconstructing full thermal status of a 16-core processor. Experimental results show that the proposed method significantly outperforms spectral analysis techniques, and can obtain full thermal characterization with an average absolute error of 1.72% using 9 thermal sensors per core.

In this paper, a new construction method of quaternary sequences of even period 2N having the ideal autocorrelation and balance properties is proposed. These quaternary sequences are constructed by applying the inverse Gray mapping to binary sequences of odd period N with the ideal autocorrelation. Autocorrelation distribution of the proposed quaternary sequences is derived. These sequences can be used to construct quaternary sequence families of even period 2N. Family size and the maximum absolute value of correlation spectrum of the proposed quaternary sequence families are also derived.

We introduce a “generalized small inverse problem (GSIP)” and present an algorithm for solving this problem. GSIP is formulated as finding small solutions of f(x0, x1, ..., xn)=x0 h(x1, ..., xn)+C=0 (mod ; M) for an n-variate polynomial h, non-zero integers C and M. Our algorithm is based on lattice-based Coppersmith technique. We provide a strategy for construction of a lattice basis for solving f=0, which is systematically transformed from a lattice basis for solving h=0. Then, we derive an upper bound such that the target problem can be solved in polynomial time in log M in an explicit form. Since GSIPs include some RSA-related problems, our algorithm is applicable to them. For example, the small key attacks by Boneh and Durfee are re-found automatically.

We propose a packet-based inverse multiplexing method to allow scalable network access with a bigger-pipe physical interface. The method is based on aggregation at the physical layer (APL) that fragments an original packet-flow and distributes the fragments among an adequate numbers of physical links or networks. It allows us to share wavelengths and/or bandwidth resources in optical networks. Its technical feasibility at the speed of newly standardized 100 Gb/s Ethernet (100 GbE) is successfully evaluated by implementing the inverse multiplexing logic functions on a prototype board. We demonstrate super-high-definition video streaming and huge file transfer by transmitting 100 GbE MAC frames over multiple 10 GbE physical links via inverse multiplexing.

Square-related functions such as square, inverse square, square-root and inverse square-root operations are widely used in digital signal processing and digital communication algorithms, and their efficient realizations are commonly required to reduce the hardware complexity. In the implementation point of view, approximate realizations are often desired if they do not degrade performance significantly. In this paper, we propose new linear approximations for the square-related functions. The traditional linear approximations need multipliers to calculate slope offsets and tables to store initial offset values and slope values, whereas the proposed approximations exploit the inherent properties of square-related functions to linearly interpolate with only simple operations, such as shift, concatenation and addition, which are usually supported in modern VLSI systems. Regardless of the bit-width of the number system, more importantly, the maximum relative errors of the proposed approximations are bounded to 6.25% and 3.13% for square and square-root functions, respectively. For inverse square and inverse square-root functions, the maximum relative errors are bounded to 12.5% and 6.25% if the input operands are represented in 20 bits, respectively.

An algorithm is formulated for reconstructing a dielectric cylinder with the use of the T-matrix and the singular value decomposition (SVD) and is discussed through numerical examples under noisy conditions. The algorithm consists of two stages. At the first stage the measured data of scattered waves is transformed into the T-matrix. At the second stage we reconstruct the cylinder from the T-matrix. The singular value decomposition is applied in order to separate the radiating and the nonradiating currents, and the radiating current is directly obtained from the T-matrix. The nonradiating current and the object are reconstructed by decreasing a residual error of the current in the least square approximation, where linear equations are solved repeatedly. Some techniques are used in order to reduce the calculation time and to reduce the effects of noise. Numerical examples show us that the presented approach is simple and numerically feasible, and enables us to reconstruct a large object in a short time.

We investigated suitable spatial inverse filters for cortical dipole imaging from the scalp electroencephalogram (EEG). The effects of incorporating statistical information of signal and noise into inverse procedures were examined by computer simulations and experimental studies. The parametric projection filter (PPF) and parametric Wiener filter (PWF) were applied to an inhomogeneous three-sphere volume conductor head model. The noise covariance matrix was estimated by applying independent component analysis (ICA) to scalp potentials. The present simulation results suggest that the PPF and the PWF provided excellent performance when the noise covariance was estimated from the differential noise between EEG and the separated signal using ICA and the signal covariance was estimated from the separated signal. Moreover, the spatial resolution of the cortical dipole imaging was improved while the influence of noise was suppressed by including the differential noise at the instant of the imaging and by adjusting the duration of noise sample according to the signal to noise ratio. We applied the proposed imaging technique to human experimental data of visual evoked potential and obtained reasonable results that coincide to physiological knowledge.

In this paper, we propose a robust room inverse filtering algorithm for speech dereverberation based on a kurtosis maximization. The proposed algorithm utilizes a new normalized kurtosis function that nonlinearly maps the input kurtosis onto a finite range from zero to one, which results in a kurtosis warping. Due to the kurtosis warping, the proposed algorithm provides more stable convergence and, in turn, better performance than the conventional algorithm. Experimental results are presented to confirm the robustness of the proposed algorithm.

We propose a scalable parallel interface that provides an ideal aggregated bandwidth link for an application. The scalable parallel interface uses time information to align packets and allows dynamic lane and/or path change, a large difference in transmission delays among lanes, and so on. The basic performance of the scalable parallel interface in 10 Gb/s 2 lanes is verified using an estimation board that is newly developed to evaluate the basic functions used in a Terabit LAN. The evaluation shows that the scalable parallel interface achieves a very low delay variation that is almost the same as that under back-to-back conditions. The difference in the delay variation between the scalable parallel interface and the back-to-back condition is approximately 10 ns when the transmission delay time varies from 10 µs to 1 s.

One major drawback of orthogonal frequency-division multiplexing is the high peak-to-average power ratio (PAPR) of the output signal. The selected mapping (SLM) and partial transmit sequences (PTS) methods are two promising techniques for PAPR reduction. However, to generate a set of candidate signals, these techniques need a bank of inverse fast Fourier transforms (IFFT's) and thus require high computational complexity. In this paper, we propose two low-complexity multiplication-free conversion processes to replace the IFFT's in the SLM method, where each conversion process for an N-point IFFT involves only 3N complex additions. Using these proposed conversions, we develop several new SLM schemes and a combined SLM & PTS method, in which at least half of the IFFT blocks are reduced. Computer simulation results show that, compared to the conventional methods, these new schemes have approximately the same PAPR reduction performance under the same number of candidate signals for transmission selection.

This paper shows that there is a fruitful world behind sampling theorems. For this purpose, the sampling problem is reformulated from a functional analytic standpoint, and is consequently revealed that the sampling problem is a kind of inverse problem. The sampling problem covers, for example, signal and image restoration including super resolution, image reconstruction from projections such as CT scanners in hospitals, and supervised learning such as learning in artificial neural networks. An optimal reconstruction operator is also given, providing the best approximation to an individual original signal without our knowing the original signal.

The IEEE802.11b WLAN standard employs direct-sequence/spread-spectrum (DS/SS) modulation. With a fractional sampling RAKE receiver, it is possible to achieve diversity and reduce the BER in DS/SS communication. In order to realize the diversity through fractional sampling, the impulse response of the channel must be estimated. In this paper, a channel estimation scheme for a RAKE receiver with fractional sampling in IEEE802.11b WLAN system is investigated through a computer simulation and an experiment. In order to estimate the impulse response of the channel, a pseudo-inverse matrix with a threshold is employed. Numerical results indicate that the channel can be estimated with an optimum threshold in both the simulation and the experiment.

An inverse scattering problem of estimating the reflection coefficient and the surface impedance from two sets of absolute values of the near field with periodic change is investigated. The problem is formulated in terms of a nonlinear simultaneous equations which is derived from the relation between the two sets of absolute values and the field defined by a finite summation of the modal functions by applying the Fourier analysis. The reflection coefficient is estimated by solving the equations by Newton's method through the successive algorithm with the increment of the number of truncation in the summation one after another. Numerical examples are given and the accuracy of the estimation is discussed.

The generalized Hamming weight played an important role in coding theory. In the study of the wiretap channel of type II, the generalized Hamming weight was extended to a two-code format. Two equivalent concepts of the generalized Hamming weight hierarchy and its two-code format, are the inverse dimension/length profile (IDLP) and the inverse relative dimension/length profile (IRDLP), respectively. In this paper, the Singleton upper bound on the IRDLP is improved by using a quotient subcode set and a subset with respect to a generator matrix, respectively. If these new upper bounds on the IRDLP are achieved, in the corresponding coordinated two-party wire-tap channel of type II, the adversary cannot learn more from the illegitimate party.

Partial transmit sequence (PTS) is a well known technique used to reduce the peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) signal. However, it has relatively high complexity due to the computation of multiple inverse fast Fourier transforms (IFFTs). To reduce this complexity, we use intermediate signals within a decimation in frequency (DIF) radix IFFT and propose a new PTS subblocking technique which requires the computation of only partial IFFTs. Performance results are presented which show a PAPR reduction similar to that with other techniques such as original PTS (O-PTS). Further, we show that complexity reduction can be achieved with either low or high radix IFFT algorithms.

Speech dereverberation is one of the most difficult tasks in acoustic signal processing. Of the various problems involved in this task, this paper highlights "over-whitening," which flattens the characteristics of recovered speech. This distortion sometimes happens when inverse filters are directly calculated from microphone signals. This paper reviews two studies related to this problem. The first study shows the possibility of compensating for such over-whitening to achieve precise speech-dereverberation. The second study presents a new approach for approximating the original speech by removing the effect of late reflections from observed reverberant speech.

A robust multichannel sound reproduction system that utilizes the relationship between the width of the actual control area and the control frequency of the control points is proposed. The reproduction accuracy of a conventional sound reproduction system is reduced by room environment variations when fixed inverse filter coefficients are used. This tendency becomes more significant when control points are arranged more closely. To resolve this problem, the frequency control band at every control point is switched to avoid degrading the reproduced sound in low frequencies, so the pass band range of the control points at both ears is only high-range. That of the other control points is the entire control range. Numerical simulation with real environmental data showed that improvement of the reproduction accuracy is about 6.1 dB on average, even with a temperature fluctuation of 5C as an environmental variation in the listening room.

High-speed wireless communication systems have attracted much attention in recent years. To achieve a high-speed wireless communication system that utilizes an ultra-wide-frequency band, a broadband antenna is required. However, it is difficult to obtain an antenna that has uniform characteristics in a broad frequency band. Moreover, propagation characteristics are distorted in a multi-path environment. Thus, the communication quality tends to degrade due to the distortion in the frequency characteristics of the wideband communication system. This paper proposes a quasi-inverse filter (QIF) to improve the compensation effect for the transmitter antenna. Furthermore, we propose a method that employs the newly developed QIF that compensates for frequency characteristic distortion. We evaluate different configurations for the compensation system employing a pre-filter and post-filter in the wideband communication system. The effectiveness of the QIF in the case of severe distortion is verified by computer simulation. The proposed method is applied to a disc monopole antenna as a concrete example of a broadband antenna, and the compensation effect for the antenna is indicated.

Further development of a network based on the Inverse Function Delayed (ID) model which can recall temporal sequences of patterns, is proposed. Additional advantage is taken of the negative resistance region of the ID model and its hysteretic properties by widening the negative resistance region and letting the output of the ID neuron be almost instant. Calling this neuron limit ID neuron, a model with limit ID neurons connected pairwise with conventional neurons enlarges the storage capacity and increases it even further by using a weightmatrix that is calculated to guarantee the storage after transforming the sequence of patterns into a linear separation problem. The network's tolerance, or the model's ability to recall a sequence, starting in a pattern with initial distortion is also investigated and by choosing a suitable value for the output delay of the conventional neuron, the distortion is gradually reduced and finally vanishes.

A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.