Human visual system can perceive 3-D structure of an object by binocular disparity, gradient of illumination (shading), occlusion, textures, perspective and so forth. Among them, binocular disparity seems to be the essentially important cues for the 3-D space perception and it is used widely for displaying 3-D visual circumstances such as in VR (virtual reality) system or 3-D TV. Visual illusions seem to be one of the phenomena which are purely reflecting the mechanism of human visual system. In the recent several years, the authors found several new types of 3-D visual illusions with binocular viewing. Entire 3-D illusory object including volume perception, transparency, dynamic illusions can be perceived only from the visual stimuli of disparity given by some inducing objects arranged with suitable relations. In this report, the authors introduced these newly found visual illusions and made some considerations on the human visual mechanism of 3-D perception and on their exploitation for new effective techniques in 3-D display. They introduced especially on the visual effect in two kinds of arrangement with occlusion and sustaining relationship between the illusory object and inducing objects. In the former case, the inducing objects which provide the stimuli were named as occlusion cues and classified into two types: contour occlusion cues and bulky occlusion cues. In the later case, those inducing objects were named as sustaining cues and a 3-D fully transparent illusory object was perceived. The perception was just like imagined from the scenes of the actions and positions of the pantomimists; then this phenomena was named as "Mime (Pantomime) Effect. " According to the positions of sustaining cues, they played different actions in this perception, and they are classified into three types: front sustaining cues, side sustaining cues and back sustaining cues. In addition, dynamic fusion and separation of volumetrical illusory objects were perceived when the visual stimuli were moving continuously between two structurally different conditions. Then the hysteresis was recognized in geometrical position between the fusion and separation. The authors believe that the occlusion cues and sustaining cues introduced in this paper could be effective clues for exploiting the new techniques for 3-D display.

Focused on network reconnaissance, eavesdropping, and DoS attacks caused by static routing policies, this paper designs a random routing mutation architecture based on the OpenFlow protocol, which takes advantages of the global network view and centralized control in a software-defined network. An entropy matrix of network traffic characteristics is constructed by using volume measurements and characteristic measurements of network traffic. Random routing mutation is triggered according to the result of network anomaly detection, which using a wavelet transform and principal component analysis to handle the above entropy matrix for both spatial and temporal correlations. The generation of a random routing path is specified as a 0-1 knapsack problem, which is calculated using an improved ant colony algorithm. Theoretical analysis and simulation results show that the proposed method not only increases the difficulty of network reconnaissance and eavesdropping but also reduces the impact of DoS attacks on the normal communication in an SDN network.

This paper investigates the resource allocation problem for the downlink of non-orthogonal multiple access (NOMA) networks. A novel resource allocation method is proposed to deal with the problem of maximizing the system capacity while taking into account user fairness. Since the optimization problem is nonconvex and intractable, we adopt the idea of step-by-step optimization, decomposing it into user pairing, subchannel and power allocation subproblems. First, all users are paired according to their different channel gains. Then, the subchannel allocation is executed by the proposed subchannel selection algorithm (SSA) based on channel priority. Once the subchannel allocation is fixed, to further improve the system capacity, the subchannel power allocation is implemented by the successive convex approximation (SCA) approach where the nonconvex optimization problem is transformed into the approximated convex optimization problem in each iteration. To ensure user fairness, the upper and lower bounds of the power allocation coefficients are derived and combined by introducing the tuning coefficients. The power allocation coefficients are dynamically adjustable by adjusting the tuning coefficients, thus the diversified quality of service (QoS) requirements can be satisfied. Finally, simulation results demonstrate the superiority of the proposed method over the existing methods in terms of system performance, furthermore, a good tradeoff between the system capacity and user fairness can be achieved.

Nyquist folding receiver (NYFR) is a novel reconnaissance receiving architecture and it can realize wideband receiving with small amount of equipment. As a tradeoff of non-cooperative wideband receiving, the NYFR output will add an unknown key parameter that is called Nyquist zone (NZ) index. In this letter, we concentrate on the NZ index estimation of the NYFR output. Focusing on the basic pulse radar signals, the constant frequency signal, the binary phase coded signal and the linear frequency modulation signal are considered. The matching component function is proposed to estimate the NZ indexes of the NYFR outputs without the prior information of the signal modulation type. In addition, the relations between the matching component function and the parameters of the NYFR are discussed. Simulation results demonstrate the efficacy of the proposed method.

The modern radar signals are in a wide frequency space. The receiving bandwidth of the radar reconnaissance receiver should be wide enough to intercept the modern radar signals. The Nyquist folding receiver (NYFR) is a novel wideband receiving architecture and it has a high intercept probability. Chirp signals are widely used in modern radar system. Because of the wideband receiving ability, the NYFR will receive the concurrent multiple chirp signals. In this letter, we propose a novel parameter estimation algorithm for the multiple chirp signals intercepted by single channel NYFR. Compared with the composite NYFR, the proposed method can save receiving resources. In addition, the proposed approach can estimate the parameters of the chirp signals even the NYFR outputs are under frequency aliasing circumstance. Simulation results show the efficacy of the proposed method.

An approach based on signal subspace analysis is proposed to blind estimation of the PN (Pseudo Noise) sequence from lower SNR (Signal to Noise Ratios) DS/SS (Direct Sequence Spread Spectrum) signals. The received signal is divided into vectors according to a temporal window, from which an autocorrelation matrix is computed and accumulated. The PN sequence can be reconstructed from principal eigenvectors of the matrix.

Particle swarm optimizer (PSO) is a stochastic global optimization technique based on a social interaction metaphor. Because of the complexity, dynamics and randomness involved in PSO, it is hard to theoretically analyze the mechanism on which PSO depends. Statistical results have shown that the probability distribution of PSO is a truncated triangle, with uniform probability across the middle that decreases on the sides. The "truncated triangle" is also called the "Maya pyramid" by Kennedy. However, very little is known regarding the sampling distribution of PSO in itself. In this paper, we theoretically analyze the "Maya pyramid" without any assumption and derive its computational formula, which is actually a hybrid uniform distribution that looks like a trapezoid and conforms with the statistical results. Based on the derived density function of the hybrid uniform distribution, the search strategy of PSO is defined and quantified to characterize the mechanism of the search strategy in PSO. In order to show the significance of these definitions based on the derived hybrid uniform distribution, the comparison between the defined search strategies of the classical linear decreasing weight based PSO and the canonical constricted PSO suggested by Clerc is illustrated and elaborated.

Aiming at traditional neural networks non-uniformity correction (NUC) algorithm's disadvantages such as slow convergence, low correction precision and difficulty to meet the real-time engineering application requirements of infrared imaging system, an improved NUC algorithm for infrared focal plane arrays (IRFPA) based on neural network is proposed. The algorithm is based on linear response of detector, and in order to realize fast and synchronization convergence of correction parameters the each original image data is normalized to a value close to one. Experimental results show the method has the faster convergence speed and better vision effect than the traditional algorithms, and it is better applied in practical projects.

Existing pose estimation algorithms suffer from either low performance or heavy computation cost. In this letter, we present an approach to improve the attractive algorithm called Orthogonal Iteration. A new form of fundamental equations is derived which reduces the computation cost significantly. And paraperspective camera model is used instead of weak perspective camera model during initialization which improves the stability. Experiment results validate the accuracy and stability of the proposed algorithm and show that its computational complexity is favorably compare to the O(n) non-iterative algorithm.

Building detection from high resolution remote sensing images is challenging due to the high intraclass variability and the difficulty in describing buildings. To address the above difficulties, a novel approach is proposed based on the combination of shape-specific feature extraction and discriminative feature classification. Shape-specific feature can capture complex shapes and structures of buildings. Discriminative feature classification is effective in reflecting similarities among buildings and differences between buildings and backgrounds. Experiments demonstrate the effectiveness of the proposed approach.

Kennedy has proposed the bare bones particle swarm (BBPS) by the elimination of the velocity formula and its replacement by the Gaussian sampling strategy without parameter tuning. However, a delicate balance between exploitation and exploration is the key to the success of an optimizer. This paper firstly analyzes the sampling distribution in BBPS, based on which we propose an adaptive BBPS inspired by the cloud model (ACM-BBPS). The cloud model adaptively produces a different standard deviation of the Gaussian sampling for each particle according to the evolutionary state in the swarm, which provides an adaptive balance between exploitation and exploration on different objective functions. Meanwhile, the diversity of the swarms is further enhanced by the randomness of the cloud model itself. Experimental results show that the proposed ACM-BBPS achieves faster convergence speed and more accurate solutions than five other contenders on twenty-five unimodal, basic multimodal, extended multimodal and hybrid composition benchmark functions. The diversity enhancement by the randomness in the cloud model itself is also illustrated.

Combining the sphere decoding (SD) algorithm and the sequential detection method, we propose an adaptive group detection (AGD) scheme based on the sort-descending QRD (S-D-QRD) for V-BLAST architectures over an i.i.d. Rayleigh flat fading channel. Simulation results show that the proposed scheme, which encompasses the SD algorithm and the sequential detection method as two extreme cases in a probability sense, can achieve a very flexible tradeoff between the detection performance and computational complexity by adjusting the group parameter.

We propose a feasible V-BLAST detector based on modified Householder QRD (M-H-QRD) over spatially correlated fading channel, which can almost match the performance of the V-BLAST algorithm with much lower complexity and better numerical stability. Compared to the sorted QRD (S-QRD) detector, the proposed detector requires a smaller minimum word-length to reach the same value of error floor for fixed-point (FP) numerical precision despite no significant performance difference for floating-point machine precision. All these advantages make it attractive when implemented using FP arithmetic.

A nonlinear piecewise scheme for non-uniformity correction in infrared focal plane arrays (IRFPA) is presented. In this method, utilizing the nonlinear piecewise scheme of detector response has extended the larger dynamic range of IRFPA response and the higher correcting accuracy than the non-uniformity correction algorithms based on linear response model of IRFPA detector. Based on the principle of this method, the mathematical model is established. At last experimental results are given out. The results show that it has higher correction precision, fewer calculations, and is easier to implement real-time non-uniformity correction of IRFPA by hardware circuit.

A fast algorithm to speed up the search process of vector quantization encoding is presented. Using the sum and the partial norms of a vector, some eliminating inequalities are constructeded. First the inequality based on the sum is used for determining the bounds of searching candidate codeword. Then, using an inequality based on subvector norm and another inequality combining the partial distance with subvector norm, more unnecessary codewords are eliminated without the full distance calculation. The proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the proposed algorithm outperforms the existing state-of-the-art search algorithms in reducing the computational complexity and the number of distortion calculation.

A simple and successful design of initial codebook of vector quantization (VQ) is presented. For existing initial codebook algorithms, such as random method, the initial codebook is strongly influenced by selection of initial codewords and difficult to match with the features of the training vectors. In the proposed method, training vectors are sorted according to the norm of training vectors. Then, the ordered vectors are partitioned into N groups where N is the size of codebook. The initial codewords are obtained from calculating the centroid of each group. This initializtion method has a robust performance and can be combined with the VQ algorithm to further improve the quality of codebook.

This letter investigates transmit optimization in multi-user multi-input multi-output (MIMO) wiretap channels. In particular, we address the transmit covariance optimization for an artificial-noise (AN)-aided secrecy rate maximization (SRM) when subject to individual harvested energy and average transmit power. Owing to the inefficiency of the conventional interior-point solvers in handling our formulated SRM problem, a custom-designed algorithm based on penalty function (PF) and projected gradient (PG) is proposed, which results in semi-closed form solutions. The proposed algorithm achieves about two orders of magnitude reduction of running time with nearly the same performance comparing to the existing interior-point solvers. In addition, the proposed algorithm can be extended to other power-limited transmit design problems. Simulation results demonstrate the excellent performance and high efficiency of the algorithm.

A fast parameter estimation method with a coarse estimation and a fine estimation for polyphase P coded signals is proposed. For a received signal with N sampling points, the proposed method has an improved performance when the signal-to-noise ratio (SNR) is larger than 2dB and a lower computational complexity O(N logs N) compared with the latest time-frequency rate estimation method whose computational complexity is O(N2).

In the scenario of finite sample size, the performance of the generalized sidelobe canceller (GSC) is still affected by the desired signal even if all signal sources are independent with each other. Firstly, the novel expression of weight vector of the auxiliary array is derived under the circumstances of finite sample size. Utilizing this new weight vector and considering the correlative interferences, the general expression for the interference cancellation ratio (CR) is developed. Then, the impacts of the CR performance are further analyzed for the parameters including the input signal-to-noise ratio (SNR), the auxiliary array size, the correlation coefficient between the desired signal and interference as well as the snapshots of the sample data, respectively. Some guidelines can thus be given for the practical application. Numerical simulations demonstrate the agreement between the simulation results and the analytical results.

This letter proposes a track before detect scheme embedded in coherent repeated interference with the aid of frequency diversity array. The unmatched properties between echo and interferences are firstly discussed from both signal processing and data processing standpoints. Afterward, the interference suppression algorithm with virtual channel weighting at continue sampling stage is proposed, followed with kinematics constraint correspondingly. Further, the evaluations of the interference suppression performance are carried out through simulations which illustrate the feasibility and validity of the proposed algorithm.