For Doppler parameter estimation of forward-looking SAR, the third-order Doppler parameter can not be neglected. In this paper, the azimuth signal of the transmitter fixed bistatic forward-looking SAR is modeled as a cubic polynomial phase signal (CPPS) and multiple time-overlapped CPPSs, and the modified cubic phase function is presented to estimate the third-order Doppler parameter. By combining the cubic phase function (CPF) with Radon transform, the method can give an accurate estimation of the third-order Doppler parameter. Simulations validate the effectiveness of the algorithm.

Constructing degree-optimized resilient Boolean functions with high nonlinearity is a significant study area in Boolean functions. In this letter, we provide a construction of degree-optimized n-variable (n odd and n ≥ 35) resilient Boolean functions, and it is shown that the resultant functions achieve the currently best known nonlinearity.

Broadband wireless networks are rapidly expanding over the world. To provide wireless broadband services for Shanghai Expo 2010, pre-research is launched and a test-bed has been developed, in which WiMAX and Wi-Fi mesh are involved. The test-bed shows that Wi-Fi mesh integrated with WiMAX is highly suitable for large-scale activities like the Olympic Games and the World Expo.

Rotation symmetric Boolean functions (RSBFs) that are invariant under circular translation of indices have been used as components of different cryptosystems. In this paper, odd-variable balanced RSBFs with maximum algebraic immunity (AI) are investigated. We provide a construction of n-variable (n=2k+1 odd and n ≥ 13) RSBFs with maximum AI and nonlinearity ≥ 2n-1-¥binom{n-1}{k}+2k+2k-2-k, which have nonlinearities significantly higher than the previous nonlinearity of RSBFs with maximum AI.

The asymmetrical halo and dual-material gate structure is used in the surrounding-gate metal-oxide-semiconductor field effect transistor (MOSFET) to improve the performance. By treating the device as three surrounding-gate MOSFETs connected in series and maintaining current continuity, a comprehensive drain current model is developed for it. The model incorporates not only channel length modulation and impact ionization effects, but also the influence of doping concentration and vertical electric field distributions. It is concluded that the device exhibits increased current drivability and improved hot carrier reliability. The derived analytical model is verified with numerical simulation.

In this paper, an analytical threshold voltage model of the strained gate-all-around MOSFET fabricated on the Si1-xGex virtual substrate is presented by solving the two-dimensional Poisson equation. The impact of key parameters such as the strain, channel length, gate oxide thickness and radius of the silicon cylinder on the threshold voltage has been investigated. It has been demonstrated that the threshold voltage decreases as the strain in the channel increases. The threshold voltage roll-off becomes severe when increasing the Ge content in the Si1-xGex virtual substrate. The model is found to tally well with the device simulator.

Parallelism on heterogeneous machines brings cost effectiveness, but also raises a new set of complex and challenging problems. This paper addresses the problem of estimating the minimum time taken to execute a program on a fine-grained parallel machine composed of different types of processors. In an earlier publication, we took the first step in this direction by presenting a graph-construction method which partitions a given program into several homogeneous parts and incorporates timing constraints due to heterogeneous parallelism into each part. In this paper, to make the method easier to be applied in a scheduling framework and to demonstrate its practical utility, we present an efficient implementation method and compare the results of its use to the optimal schedule lengths obtained by enumerating all possible solutions. Experimental results for several different machine models indicate that this method can be effectively used to estimate a program's minimum execution time.

As a consequence of recent developments in communications, the parameters of communication signals, such as the modulation parameter values, are becoming unstable because of time-varying SNR under electromagnetic conditions. In general, it is difficult to classify target signals that have time-varying parameters using traditional signal recognition methods. To overcome this problem, this study proposes a novel recognition method that works well even for such time-dependent communication signals. This method is mainly composed of feature extraction and classification processes. In the feature extraction stage, we adopt Shannon entropy and index entropy to obtain the stable features of modulated signals. In the classification stage, the interval gray relation theory is employed as suitable for signals with time-varying parameter spaces. The advantage of our method is that it can deal with time-varying SNR situations, which cannot be handled by existing methods. The results from numerical simulation show that the proposed feature extraction algorithm, based on entropy characteristics in time-varying SNR situations,offers accurate clustering performance, and the classifier, based on interval gray relation theory, can achieve a recognition rate of up to 82.9%, even when the SNR varies from -10 to -6 dB.