Estimation and detection algorithms for orthogonal frequency division multiplexing (OFDM) systems can be developed based on the sum-product algorithms, which operate by message passing in factor graphs. In this paper, we apply the sampling method (Monte Carlo) to factor graphs, and then the integrals in the sum-product algorithm can be approximated by sums, which results in complexity reduction. The blind receiver for OFDM systems can be derived via Sequential Monte Carlo (SMC) in factor graphs, the previous SMC blind receiver can be regarded as the special case of the sum-product algorithms using sampling methods. The previous SMC blind receiver for OFDM systems needs generating samples of the channel vector assuming the channel has an a priori Gaussian distribution. In the newly-built blind receiver, we generate samples of the virtual-pilots instead of the channel vector, with channel vector which can be easily computed based on virtual-pilots. As the size of the virtual-pilots space is much smaller than the channel vector space, only small number of samples are necessary, with the blind detection being much simpler. Furthermore, only one pilot tone is needed to resolve phase ambiguity and differential encoding is not used anymore. Finally, the results of computer simulations demonstrate that the proposal can perform well while providing significant complexity reduction.

A novel cell search scheme for OFDM cellular systems is proposed. It is based on one OFDM symbol with several identical slots as preamble, the time domain repetition structure of which can be utilized to accomplish OFDM timing/frequency synchronization. The cell ID is comprised of two parts: a sub-carrier mask index g and a sequence index x. Each sub-carrier mask activates or deactivates some of the sub-carriers, after which a differentially coded sequence is loaded on pairs of the adjacent active sub-carriers. The user equipment (UE) recognizes the mask with index g via power detection of the received frequency domain signal. Then it estimates the index x from differential demodulation followed by detection of the frequency domain sequence. In order to improve the performance, a method of jointly estimating g and x is devised. Simulation results showed that the proposed scheme is able to support a very large number of cell IDs while maintaining a good performance even in bad multi-cell environment.

In this paper, we propose an analytical model for the performance evaluation of IEEE 802.11e enhanced distributed channel access (EDCA). Different from most previous analytical studies based on the saturation assumption, we extend the analytical model to non-saturation conditions. An empty state is introduced into the Markov chain to represent the status of transmission queue being empty. This model can be used to calculate the traffic priority, throughput, and MAC layer delay with various configurations of contention parameters. A detailed simulation is provided to validate the proposed model. With the help of this model, the contention parameters can be configured appropriately to achieve specific quality-of-service (QoS) requirements.

It is well known that interleavers play a critical role in Turbo coding/decoding schemes, and contention-free interleaver design has become a serious problem in the parallelization of Turbo decoding, which is indispensable to meet the demands for high throughput and low latency in next generation mobile communication systems. This paper unveils the fact that interleavers based on permutation polynomials modulo N are contention-free for every window size W, a factor of the interleaver length N, which, also called maximum contention-free interleavers.

This paper details on the design of DVB-S2 receivers which is compliant with the broadcasting mode. Special attention is paid to the specific receiver functions necessary to demodulate the received signal. To show the system performance we consider the design of a complete receiver consisting of timing recovery unit, frame synchronization unit, frequency recovery unit and phase recovery unit. The system is easier to hardware implementation comparing with that provided in (ETSI, 2005; Sun et al., 2004). After the performance of the algorithms is analyzed and a quantitative result is given, this allows us to draw conclusions concerning the achievable system performance under realistic complexity assumptions.

This paper presents a macroblock-level (MB-level) decoding and deblocking method for supporting the flexible macroblock ordering (FMO) and arbitrary slice ordering (ASO) bit streams in H.264 decoder and its SOC/ASIC implementation. By searching the slice containing the current macroblock in the bit stream and switching slices correctly, MBs can be decoded in the raster scan order, while the decoding process can immediately begin as long as the slice containing the current MB is available. This architectural modification enables the MB-level decoding and deblocking 3-stage pipeline, and saves about 20% of SDRAM bandwidth. Implementation results showed that the design achieves real-time decoding of 1080HD (1920×1088@30 fps) at a system clock of 166 MHz.

In order to improve the efficiency of embedded software running on processor core, this paper proposes a hardware/software co-optimization approach for embedded software from the system point of view. The proposed stepwise methods aim at exploiting the structure and the resources of the processor as much as possible for software algorithm optimization. To achieve low memory usage and low frequency need for the same performance, this co-optimization approach was used to optimize embedded software of MP3 decoder based on a 16-bit fixed-point DSP core. After the optimization, the results of decoding 128 kbps, 44.1 kHz stereo MP3 on DSP evaluation platform need 45.9 MIPS and 20.4 kbytes memory space. The optimization rate achieves 65.6% for memory and 49.6% for frequency respectively compared with the results by compiler using floating-point computation. The experimental result indicates the availability of the hardware/software co-optimization approach depending on the algorithm and architecture.

A novel topology low-voltage high precision current reference based on subthreshold Metal-Oxide-Semiconductor Field Effect Transistors (MOSFETs) is presented. The circuit achieves a temperature-independent reference current by a proper combination current of two first-order temperature-compensation current references, which exploit the temperature characteristics of integrated poly2 resistors and the I-V transconductance characteristics of MOSFET operating in the subthreshold region. The circuit, designed with the 1st silicon 0.35 µm standard CMOS logic process technology, exhibits a stable current of about 2.25 µA with much low temperature coefficient of 3×10⁻⁴ µA/°C in the temperature range of −40~150 °C at 1 V supply voltage, and also achieves a better power supply rejection ratio (PSRR) over a broad frequency. The PSRR is about −78 dB at DC and remains −42 dB at the frequency higher than 10 MHz. The maximal process error is about 6.7% based on the Monte Carlo simulation. So it has good process compatibility.

A new framework of region-based dynamic image fusion is proposed. First, the technique of target detection is applied to dynamic images (image sequences) to segment images into different targets and background regions. Then different fusion rules are employed in different regions so that the target information is preserved as much as possible. In addition, steerable non-separable wavelet frame transform is used in the process of multi-resolution analysis, so the system achieves favorable characters of orientation and invariant shift. Compared with other image fusion methods, experimental results showed that the proposed method has better capabilities of target recognition and preserves clear background information.

We present a robust connected-component (CC) based method for automatic detection and segmentation of text in real-scene images. This technique can be applied in robot vision, sign recognition, meeting processing and video indexing. First, a Non-Linear Niblack method (NLNiblack) is proposed to decompose the image into candidate CCs. Then, all these CCs are fed into a cascade of classifiers trained by Adaboost algorithm. Each classifier in the cascade responds to one feature of the CC. Proposed here are 12 novel features which are insensitive to noise, scale, text orientation and text language. The classifier cascade allows non-text CCs of the image to be rapidly discarded while more computation is spent on promising text-like CCs. The CCs passing through the cascade are considered as text components and are used to form the segmentation result. A prototype system was built, with experimental results proving the effectiveness and efficiency of the proposed method.

This paper presents a multi-face detection method for color images. The method is based on the assumption that faces are well separated from the background by skin color detection. These faces can be located by the proposed method which modifies the subtractive clustering. The modified clustering algorithm proposes a new definition of distance for multi-face detection, and its key parameters can be predetermined adaptively by statistical information of face objects in the image. Downsampling is employed to reduce the computation of clustering and speed up the process of the proposed method. The effectiveness of the proposed method is illustrated by three experiments.

Automatic Chinese text summarization for dialogue style is a relatively new research area. In this paper, Latent Semantic Analysis (LSA) is first used to extract semantic knowledge from a given document, all question paragraphs are identified, an automatic text segmentation approach analogous to TextTiling is exploited to improve the precision of correlating question paragraphs and answer paragraphs, and finally some “important” sentences are extracted from the generic content and the question-answer pairs to generate a complete summary. Experimental results showed that our approach is highly efficient and improves significantly the coherence of the summary while not compromising informativeness.

Applying ontology to describe resource metadata richly in the peer-to-peer environment has become current research trend. In this semantic peer-to-peer environment, indexing semantic element of resource description to support efficient resource location is a difficult and challenging problem. This paper provided a hybrid indexing architecture, which combines local indexing and global indexing. It uses community strategy and semantic routing strategy to organize key layer metadata element and uses DHT (distributed hash table) to index extensional layer metadata element. Compared with related system, this approach is more efficient in resource location and more scalable.

Job management is a key issue in computational grids, and normally involves job definition, scheduling, executing and monitoring. However, job management in the existing grid middleware needs to be improved in terms of efficiency and flexibility. This paper addresses a flexible architecture for job management with detailed design and implementation. Frameworks for job scheduling and monitoring, as two important aspects, are also presented. The proposed job management has the advantages of reusability of job definition, flexible and automatic file operation, visual steering of file transfer and job execution, and adaptive application job scheduler. A job management wizard is designed to implement each step. Therefore, what the grid user needs to do is only to define the job by constructing necessary information at runtime. In addition, the job space is adopted to ensure the security of the job management. Experimental results showed that this approach is user-friendly and system efficient.

Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.

It was shown that active queue management schemes implemented in the routers of communication networks supporting transmission control protocol (TCP) flows can be modelled as a feedback control system. In this paper based on Lyapunov function we developed an optimal controller to improve active queue management (AQM) router’s stability and response time, which are often in conflict with each other in system performance. Ns-2 simulations showed that optimal controller outperforms PI controller significantly.

Scheduling chain combination is the core of chain-based scheduling algorithms, the speed of which determines the overall performance of corresponding scheduling algorithm. However, backtracking is used in general combination algorithms to traverse the whole search space which may introduce redundant operations, so performance of the combination algorithm is generally poor. A fast scheduling chain combination algorithm which avoids redundant operations by skipping “incompatible” steps of scheduling chains and using a stack to remember the scheduling state is presented in this paper to overcome the problem. Experimental results showed that it can improve the performance of scheduling algorithms by up to 15 times. By further omitting unnecessary operations, a fast algorithm of minimum combination length prediction is developed, which can improve the speed by up to 10 times.

In this paper we investigate a variant of the scheduling problem on two uniform machines with speeds 1 and s. For this problem, we are given two potential uniform machines to process a sequence of independent jobs. Machines need to be activated before starting to process, and each machine activated incurs a fixed machine activation cost. No machines are initially activated, and when a job is revealed, the algorithm has the option to activate new machines. The objective is to minimize the sum of the makespan and the machine activation cost. We design optimal online algorithms with competitive ratio of (2s+1)/(s+1) for every s≥1.

In order to further enrich the form of 3D Mandelbrot and Julia sets, this paper first presents two methods of generating 3D fractal sets by utilizing discrete modifications of the standard quaternion algebra and analyzes the limitations in them. To overcome these limitations, a novel method for generating 3D fractal sets based on a 3D number system named ternary algebra is proposed. Both theoretical analyses and experimental results demonstrate that the ternary-algebra-based method is superior to any one of the quad-algebra-based methods, including the first two methods presented in this paper, because it is more intuitive, less time consuming and can completely control the geometric structure of the resulting sets. A ray-casting algorithm based on period checking is developed with the goal of obtaining high-quality fractal images and is used to render all the fractal sets generated in our experiments. It is hoped that the investigations conducted in this paper would result in new perspectives for the generalization of 3D Mandelbrot and Julia sets and for the generation of other deterministic 3D fractals as well.

The construction of the biproduct of Hopf algebras, which consists of smash product and the dual notion of smash coproduct, was first formulated by Radford. In this paper we study the quasitriangular structures over biproduct Hopf algebras B*H. We show the necessary and sufficient conditions for biproduct Hopf algebras to be quasitriangular. For the case when they are, we determine completely the unique formula of the quasitriangular structures. And so we find a way to construct solutions of the Yang-Baxter equation over biproduct Hopf algebras in the sense of (Majid, 1990).

Let Z=(Z_t)_t≥0 be a Bessel process of dimension δ (δ>0) starting at zero and let K(t) be a differentiable function on [0, ∞) with K(t)>0 (∀t≥0). Then we establish the relationship between L^p-norm of log^1/2(1+δJ_τ) and L^p-norm of sup Z_t[t+k(t)]^–1/2 (0≤t≤τ) for all stopping times τ and all 0<p<+∞. As an interesting example, we show that ||log^1/2(1+δL_m+1(τ))||_p and ||supZ_t∏[1+L_j(t)]^–1/2||_p (0≤j≤m, j∈Ζ; 0≤t≤τ) are equivalent with 0<p<+∞ for all stopping times τ and all integer numbers m, where the function L_m(t) (t≥0) is inductively defined by L_m+1(t)=log[1+L_m(t)] with L₀(t)=1.

This paper develops mathematically and empirically tractable regional and interregional model of economic development with increasing returns to scale (IRS) under the neoclassical assumptions. A one-sector, two-region model in which one region exhibits IRS is presented and the whole nation presents constant returns to scale. The development of the local IRS economy is shown to be constrained to a “moving equilibrium” path. The preliminary empirical results are sufficiently supportive of the argument to encourage further research along the lines of the model. In particular, the neoclassical model does not predict negative coefficients on the real rental value of capital in regressions explaining population or employment relative to that in the nation.