This paper presents the design of a multiple-standard 1080 high definition (HD) video decoder on a mixed-grained reconfigurable computing platform integrating coarse-grained reconfigurable processing units (RPUs) and FPGAs. The proposed RPU, including 16×16 multi-functional processing elements (PEs), is used to accelerate compute-intensive tasks in the video decoding. A soft-core-based microprocessor array is implemented on the FPGA and adopted to speed-up the dynamic reconfiguration of the RPU. Furthermore, a mail-box-based communication scheme is utilized to improve the communication efficiency between RPUs and FPGAs. By exploiting dynamic reconfiguration of the RPUs and static reconfiguration of the FPGAs, the proposed platform achieves scalable performances and cost trade-offs to support a variety of video coding standards, including MPEG-2, AVS, H.264, and HEVC. The measured results show that the proposed platform can support H.264 1080 HD video streams at up to 57 frames per second (fps) and HEVC 1080 HD video streams at up to 52fps under 250MHz, at the same time, it achieves a 3.6× performance gain over an industrial coarse-grained reconfigurable processor for H.264 decoding, and a 6.43× performance boosts over a general purpose processor based implementation for HEVC decoding.

This paper proposes a new class of Hilbert pairs of almost symmetric orthogonal wavelet bases. For two wavelet bases to form a Hilbert pair, the corresponding scaling lowpass filters are required to satisfy the half-sample delay condition. In this paper, we design simultaneously two scaling lowpass filters with the arbitrarily specified flat group delay responses at ω=0, which satisfy the half-sample delay condition. In addition to specifying the number of vanishing moments, we apply the Remez exchange algorithm to minimize the difference of frequency responses between two scaling lowpass filters, in order to improve the analyticity of complex wavelets. The equiripple behavior of the error function can be obtained through a few iterations. Therefore, the resulting complex wavelets are orthogonal and almost symmetric, and have the improved analyticity. Finally, some examples are presented to demonstrate the effectiveness of the proposed design method.

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.

In this paper, a vehicular antenna design scheme that considers vehicular body effects is proposed. A wire antenna for the global positioning system (GPS) and long-term evolution (LTE) systems is implemented on a plastic plate and then mounted on a windshield of the vehicle. Common outputs are used to allow feed sharing. It is necessary to increase the GPS right-hand circularly polarization (RHCP) gain near the zenith and to reduce the axis ratio (AR). For LTE, we need to increase the horizontal polarization (HP) gain. In addition, for LTE, multiband characteristics are required. In order to achieve the specified performance, the antenna shape is optimized via a Pareto genetic algorithm (PGA). When an antenna is mounted on the body, antenna performance changes significantly. To evaluate the performance of an antenna with complex shape mounted on a windshield, a commercial electromagnetic simulator (Ansoft HFSS) is used. To apply electromagnetic results output by HFSS to the PGA algorithm operating in the MATLAB environment, a MATLAB-to-HFSS linking program via Visual BASIC (VB) script was used. It is difficult to carry out the electromagnetic analysis on the entire body because of the limitations of the calculating load and memory size. To overcome these limitations, we consider only that part of the vehicle's body that influences antenna performance. We show that a series of optimization steps can minimize the degradation caused by the vehicle`s body. The simulation results clearly show that it is well optimized at 1.575GHz for GPS, and 0.74 ∼ 0.79GHz and 2.11 ∼ 2.16GHz for LTE, respectively.

A partitioning parallelization of the multi-objective evolutionary algorithm based on decomposition, pMOEA/D, is proposed in this letter to achieve significant time reductions for expensive bi-objective optimization problems (BOPs) on message-passing clusters. Each sub-population of pMOEA/D resides on a separate processor in a cluster and consists of a non-overlapping partition and some extra overlapping individuals for updating neighbors. Additionally, sub-populations cooperate across separate processors by the hybrid migration of elitist individuals and utopian points. Experimental results on two benchmark BOPs and the wireless sensor network layout problem indicate that pMOEA/D achieves satisfactory performance in terms of speedup and quality of solutions on message-passing clusters.

This paper presents novel reconfigurable semi-systolic array architecture for the Smith-Waterman with an affine gap penalty algorithm to align protein sequences optimized for shorter database sequences. This architecture has been modified to enable hardware reuse rather than replicating processing elements of the semi-systolic array in multiple FPGAs. The proposed hardware architecture and the previously published conventional one are described at the Register Transfer Level (RTL) using VHDL language and implemented using the FPGA technology. The results show that the proposed design has significant higher normalized speedup (up to 125%) over the conventional one for query sequence lengths less than 512 residues. According to the UniProtKB/TrEMBL protein database (release 2015_05) statistics, the largest number of sequences (about 80%) have sequence length less than 512 residues that makes the proposed design outperforms the conventional one in terms of speed and area in this sequence lengths range.

A projective Reed-Muller (PRM) code, obtained by modifying a Reed-Muller code with respect to a projective space, is a doubly extended Reed-Solomon code when the dimension of the related projective space is equal to 1. The minimum distance and the dual code of a PRM code are known, and some decoding examples have been presented for low-dimensional projective spaces. In this study, we construct a decoding algorithm for all PRM codes by dividing a projective space into a union of affine spaces. In addition, we determine the computational complexity and the number of correctable errors of our algorithm. Finally, we compare the codeword error rate of our algorithm with that of the minimum distance decoding.

To improve the performance of capsule endoscope, it is important to add location information to the image data obtained by the capsule endoscope. There is a disadvantage that a lot of existing localization techniques require to measure channel model parameters in advance. To avoid such a troublesome pre-measurement, this paper pays attention to capsule endoscope localization based on an electromagnetic imaging technology which can estimate not only the location but also the internal structure of a human body. However, the electromagnetic imaging with high resolution has huge computational complexity, which should prevent us from carrying out real-time localization. To ensure the accurate real-time localization system without pre-measured model parameters, we apply genetic algorithm (GA) into the electromagnetic imaging-based localization method. Furthermore, we evaluate the proposed GA-based method in terms of the simulation time and the location estimation accuracy compared to the conventional methods. In addition, we show that the proposed GA-based method can perform more accurately than the other conventional methods, and also, much less computational complexity of the proposed method can be accomplished than a greedy algorithm-based method.

We consider a problem as follows: Given unit weights arriving in an online manner with the total cardinality unknown, upon each arrival we decide where to place it on the unit circle in $mathbb{R}^{2}$. The objective is to set the center of mass of the placed weights as close to the origin as possible. We apply competitive analysis defining the competitive difference as a performance measure. We first present an optimal strategy for placing unit weights which achieves a competitive difference of $rac{1}{5}$. We next consider a variant in which the destination of each weight must be chosen from a set of positions that equally divide the unit circle. We give a simple strategy whose competitive difference is 0.35. Moreover, in the offline setting, several conditions for the center of mass to lie at the origin are derived.

We consider a problem of the choice of price plans offered by a telecommunications company: a “pay-as-you-go” plan and a “flat-rate” plan. This problem is formulated as an online optimization problem extending the ski-rental problem, and analyzed using the competitive ratio. We give a lemma for easily calculating the competitive ratio. Based on the lemma, we derive a family of optimal strategies for a realistic class of instances.

In this paper, we consider the problem of generating uniformly random mosaic floorplans. We propose a polynomial-time algorithm that generates such floorplans with f faces. Two modified algorithms are created to meet additional criteria.

In this paper we present a novel treatment of cellular automata (CA) from an algebraic point of view. CA on monoids associated with Σ-algebras are introduced. Then an extension of Hedlund's theorem which connects CA associated with Σ-algebras and continuous functions between prodiscrete topological spaces on the set of configurations are discussed.

Suppose that we are given two vertex covers C0 and Ct of a graph G, together with an integer threshold k ≥ max{|C0|, |Ct|}. Then, the vertex cover reconfiguration problem is to determine whether there exists a sequence of vertex covers of G which transforms C0 into Ct such that each vertex cover in the sequence is of cardinality at most k and is obtained from the previous one by either adding or deleting exactly one vertex. This problem is PSPACE-complete even for planar graphs. In this paper, we first give a linear-time algorithm to solve the problem for even-hole-free graphs, which include several well-known graphs, such as trees, interval graphs and chordal graphs. We then give an upper bound on k for which any pair of vertex covers in a graph G has a desired sequence. Our upper bound is best possible in some sense.

The new generation video standard, i.e., High-efficiency Video Coding (HEVC), shows a significantly improved efficiency relative to the last standard, i.e., H.264. However, the quad tree structured coding units (CUs), which are adopted in HEVC to improve compression efficiency, cause high computational complexity. In this study, a novel fast algorithm is proposed for CU partition in intra coding to reduce the computational complexity. A rough minimum depth prediction of the largest CU method and an early termination method for CU partition based on the total coding bits of the current CU are employed. Many approaches have been proposed to reduce the encoding complexity of HEVC, but these methods do not use the total coding bits of the current CU as the main basis for judgment to judge the CU complexity. Compared with the reference software HM16.6, the proposed algorithm reduces encoding time by 45% on average and achieves an approximately 1.1% increase in Bjntegaard delta bit rate and a negligible peak signal-to-noise ratio loss.

This paper describes a fast and effective algorithm for refining the parameter estimates of multicomponent third-order polynomial phase signals (PPSs). The efficiency of the proposed algorithm is accompanied by lower signal-to-noise ratio (SNR) threshold, and computational complexity. A two-step procedure is used to estimate the parameters of multicomponent third-order PPSs. In the first step, an initial estimate for the phase parameters can be obtained by using fast Fourier transformation (FFT), k-means algorithm and three time positions. In the second step, these initial estimates are refined by a simple moving average filter and singular value decomposition (SVD). The SNR threshold of the proposed algorithm is lower than those of the non-linear least square (NLS) method and the estimation refinement method even though it uses a simple moving average filter. In addition, the proposed method is characterized by significantly lower complexity than computationally intensive NLS methods. Simulations confirm the effectiveness of the proposed method.

In this letter, we propose a blind adaptive algorithm for joint compensation of inter-block interference (IBI) and frequency-dependent IQ imbalance using a single time-domain equalizer. We combine the MERRY algorithm for IBI suppression with the differential constant modulus algorithm to compensate for IQ imbalance. The effectiveness of the proposed algorithm is shown through computer simulations.

In the literature, many cryptosystems have been proposed to be secure under the Strong Diffie-Hellman (SDH) and related problems. For example, there is a cryptosystem that is based on the SDH/related problem or allows the Diffie-Hellman oracle. If the cryptosystem employs general domain parameters, this leads to a significant security loss caused by Cheon's algorithm [14], [15]. However, all elliptic curve domain parameters explicitly recommended in the standards (e.g., ANSI X9.62/63 [1], [2], FIPS PUB 186-4 [43], SEC 2 [50], [51]) are susceptible to Cheon's algorithm [14], [15]. In this paper, we first prove that (q-1)(q+1) is always divisible by 24 for any prime order q>3. Based on this result and depending on small divisors d1,d2≤(log q)2, we classify primes q>3, such that both (q-1)/d1 and (q+1)/d2 are primes, into Perfect, Semiperfect, SEC1v2 and Acceptable. Then, we describe algorithmic procedures and show their simulation results of secure elliptic curve domain parameters over prime/character 2 finite fields resistant to Cheon's algorithm [14], [15]. Also, several examples of the secure elliptic curve domain parameters (including Perfect or Semiperfect prime q) are followed.

Cassuto and Blaum presented a new coding framework for channels whose outputs are overlapping pairs of symbols in storage applications. Such channels are called symbol-pair read channels. Pair distance and pair error are used in symbol-pair read channels. Yaakobi et al. proved a lower bound on the minimum pair distance of cyclic codes. Furthermore, they provided a decoding algorithm for correcting pair errors using a decoder for cyclic codes, and showed the number of pair errors that can be corrected by their algorithm. However, their algorithm cannot correct all pair error vectors within half of the minimum pair distance. In this paper, we propose an efficient decoding algorithm for cyclic codes over symbol-pair read channels. It is based on the relationship between pair errors and syndromes. In addition, we show that the proposed algorithm can correct more pair errors than Yaakobi's algorithm.

In this paper, we investigate the security property of RSA when some middle bits of the private key d are known to an attacker. Using the technique of unravelled linearization, we present a new attack on RSA with known middle bits, which improves a previous result under certain circumstance. Our approach is based on Coppersmith's method for finding small roots of modular polynomial equations.

We present numerical results on the rate-distortion performance of convolutional coding for the binary symmetric source, and show how convolutional codes approach the rate-distortion bound by increasing the trellis states.