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.

This paper is focused on discussing a low-voltage system for lightning, and in particular the testing equipment of surge arresters. Only by demonstrating the performance and applicability of arresters can we seek the most feasible and economic low-voltage solutions. After performing repeated experiments with the same testing samples, using different testing equipment, we compare the different test results in order to select the most suitable and applicable testing equipment. In addition, the basis of a surge current parameter design theory is confirmed and verified through the test results using a simple and compact Impulse Current Generator to test a wide range of samples. By performing the actual analyzes and experiments, we can understand deeply how R, L, and C affect surge current, current wave, and current wave time. The ideal testing equipment standards have been set as follows: (1) Test Voltage up to 20 kV; (2) Expand current range from 1.5 kA to 46.5 kA, with resolution 1.5 kA; and (3) Simple operational procedures.

In this study, flexible organic solar cells (OSCs) employing a solution-processed hole-transporting layer (HTL) and low temperature annealing active layer have been fabricated. Vanadium oxide (V$_{2}$O$_{5})$, poly(3,4-ethylene dioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), V$_{2}$O$_{5}$/PEDOT:PSS or PEDOT:PSS/V$_{2}$O$_{5}$ is used as the HTL. Poly(3-hexythiophene) (P3HT):[6,6]-phenyl C61-butyric acid methyl ester (PCBM) is used as the active layer. HTL and active layer are all formed by a spin coating method on polyethylene terephthalate (PET) substrates. The OSC configuration has been optimized in the study to be PET/ITO/V$_{2}$O$_{5}$/PEDOT:PSS/P3HT:PCBM/LiF/Al. Based on a low annealing temperature of 90$^{circ}$C for P3HT:PCBM and parameters optimization of solution-processed V$_{2}$O$_{5}$/PEDOT:PSS, the OSC demonstrates a current density (JSC) and power conversion efficiency (PCE) of 6.08, mA/cm$^{2}$ and 1.57%, while an OSC without the HTL has PCE around 0.06%. The V$_{2}$O$_{5}$/PEDOT:PSS stacked HTL provides not only a stepwise hole-transporting energy diagram configuration but a smooth film surface for coating P3HT:PCBM active layer, which subsequently increases charge carrier transporting capability and extracts holes from the active layer to the anode.

Heterogeneous Small Cell Network (HSCN) will have wide application given its ability to improve system capacity and hot spot coverage. In order to increase the efficiency of spectrum and energy, a great deal of research has been carried out on radio resource management in HSCN. However, it is a remarkable fact that the user experience in terms of traffic rate demands has been neglected in existing research with excessive concentration on network capacity and energy efficiency. In this paper, we redefined the energy efficiency (EE) and formulate the joint optimization problem of user experience and energy efficiency maximization into a mixed integer non-linear programming (MINLP) problem. After reformulating the optimization problem, the joint subchannel (SC) allocation and power control algorithm is proposed with the help of cluster method and genetic algorithm. Simulation results show that the joint SC allocation and power control algorithm proposed has better performance in terms of user experience and energy consumption than existing algorithms.

This paper investigates dynamic spectrum access based on MAC-Layer spectrum sensing and prior channel pre-allocation strategy. We first combine channel utilization with channel state transition probability from idle to busy to reflect the channel opportunity quality in cognitive radio systems. Then a MAC-Layer spectrum sensing algorithm based on Channel Opportunity Quality Descending Order (COQDO) is proposed for the single secondary user scenario, so that the single secondary user can be provided with dynamic spectrum access. For the multi-secondary users scenario, in order to solve the channel collision problem among secondary users in dynamic spectrum access, a joint MAC-Layer spectrum sensing and prior channel pre-allocation algorithm is proposed and analyzed. Channel collision problem occurs when more than one secondary users detect the channel as idle and access it at the same time. Furthermore, the prior channel pre-allocation is optimized by using the conventional Color Sensitive Graph Coloring (CSGC) algorithm. Extensive simulation results are presented to compare our proposed algorithms with existing algorithms in terms of idle channel search delay and accumulated channel handoff delay.

Breast cancer is a serious disease across the world, and it is one of the largest causes of cancer death for women. The traditional diagnosis is not only time consuming but also easily affected. Hence, artificial intelligence (AI), especially neural networks, has been widely used to assist to detect cancer. However, in recent years, the computational ability of a neuron has attracted more and more attention. The main computational capacity of a neuron is located in the dendrites. In this paper, a novel neuron model with dendritic nonlinearity (NMDN) is proposed to classify breast cancer in the Wisconsin Breast Cancer Database (WBCD). In NMDN, the dendrites possess nonlinearity when realizing the excitatory synapses, inhibitory synapses, constant-1 synapses and constant-0 synapses instead of being simply weighted. Furthermore, the nonlinear interaction among the synapses on a dendrite is defined as a product of the synaptic inputs. The soma adds all of the products of the branches to produce an output. A back-propagation-based learning algorithm is introduced to train the NMDN. The performance of the NMDN is compared with classic back propagation neural networks (BPNNs). Simulation results indicate that NMDN possesses superior capability in terms of the accuracy, convergence rate, stability and area under the ROC curve (AUC). Moreover, regarding ROC, for continuum values, the existing 0-connections branches after evolving can be eliminated from the dendrite morphology to release computational load, but with no influence on the performance of classification. The results disclose that the computational ability of the neuron has been undervalued, and the proposed NMDN can be an interesting choice for medical researchers in further research.

With appropriate geometry configurations, bistatic Synthetic Aperture Radar (SAR) can break through the limitations of monostatic SAR for forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. This paper develops a frequency-domain imaging algorithm for translational invariant BFSAR. The algorithm uses the method of Lengendre polynomials expansion to compute the two dimensional point target reference spectrum, and this spectrum is used to perform the range cell migration correction (RCMC), secondary range compression and azimuth compression. In particular, the Doppler-centroid and bistatic-range dependent interpolation for residual RCMC is presented in detail. In addition, a method that combines the ambiguity and resolution theories to determine the forward-looking imaging swath is also presented in this paper.

Tonal signals are shown as spectral peaks in the frequency domain. When the number of spectral peaks is small and the spectral signal is sparse, Compressive Sensing (CS) can be adopted to locate the peaks with a low-cost sensing system. In the CS scheme, a time domain signal is modelled as $oldsymbol{y}=Phi F^{-1}oldsymbol{s}$, where y and s are signal vectors in the time and frequency domains. In addition, F-1 and $Phi$ are an inverse DFT matrix and a random-sampling matrix, respectively. For a given y and $Phi$, the CS method attempts to estimate s with l0 or l1 optimization. To generate the peak candidates, we adopt the frequency-domain information of $ esmile{oldsymbol{s}}$ = $oldsymbol{F} esmile{oldsymbol{y}}$, where $ esmile{y}$ is the extended version of y and $ esmile{oldsymbol{y}}left(oldsymbol{n} ight)$ is zero when n is not elements of CS time instances. In this paper, we develop Gaussian statistics of $ esmile{oldsymbol{s}}$. That is, the variance and the mean values of $ esmile{oldsymbol{s}}left(oldsymbol{k} ight)$ are examined.

For medical imaging, non-rigid motion analysis of the heart deformability is a nontrivial problem. This paper introduces a new method to analyze the gated SPECT (Single Photon Emission Computed Tomography) imges for 3-D motion information of left ventricular. Our motion estimation method is based on a new concept called normal direction constraint" in that the normal of a surface patch of some deforming objects at certain time instant is constant. This paper consists of the following processes: contour extraction, slices interpolation, normal vector field generation, expanding process, motion estimation for producing a 2-D motion vector field, and deprojection for a 3-D motion vector field. In the experiments, we will demonstrate the accuracy of our method in analyzing the 3-D motion field of deforming object.

Cooperative communication provides a new way of introducing spatial diversity to wireless systems. In order to increase the spectral efficiency of coded cooperative relaying system, the adaptive modulation technique is presented under Rayleigh fading channel in this paper. The source and relay adapt their modulation schemes based on the channel condition of all three links, i.e. source to relay, source to destination and relay to destination. Furthermore, since the available channel knowledge of the source to relay link is usually non-ideal at the destination in practice, a simplified estimation of this link quality is also given. Simulation demonstrates the effectiveness of the proposed technique in improving the data throughput.

Bistatic synthetic aperture radar (BSAR) with one fixed station (OF-BSAR) can be used in wide area surveillance, ground moving target indication etc. This paper analyzes the spatial variance of OF-BSAR. Analytical expressions of the spatial invariance region in the data space are given. Using these results, we can determine the spatial invariance region in the data set and the imaging area. After that, we give a data blocking scheme for raw data focusing. Numerical simulation verifies the results of this paper.

This paper presents a modified disparity measurement to recover the depth and a robust method to estimate motion parameters. First, this paper considers phase correspondence for the computation of disparity. It has less computation for disparity than previous methods that use the disparity from correspondence and from correlation. This modified disparity measurement uses the Gabor filter to analyze the local phase property and the exponential filter to analyze the global phase property. These two phases are added to make quasi-linear phases of the stereo image channels which are used for the stereo disparity finding and the structure recovery of scene. Then, we use feature-based correspondence to find the corresponding feature points in temporal image pair. Finally, we combine the depth map and use disparity motion stereo to estimate 3-D motion parameters.

Face detection from cluttered images is very challenging due to the wide variety of faces and the complexity of image backgrounds. In this paper, we propose a neural network based approach for locating frontal views of human faces in cluttered images. We use a radial basis function network (RBFN) for separation of face and non-face patterns, and the complexity of RBFN is reduced by principal component analysis (PCA). The influence of the number of hidden units and the configuration of basis functions on the detection performance was investigated. To further improve the performance, we integrate the distance from feature subspace into the RBFN. The proposed method has achieved high detection rate and low false positive rate on testing a large number of images.

We present a novel adversarial, end-to-end framework based on Creative-GAN to generate artistic music conditioned on dance videos. Our proposed framework takes the visual and motion posture data as input, and then adopts a quantized vector as the audio representation to generate complex music corresponding to input. However, the GAN algorithm just imitate and reproduce works what humans have created, instead of generating something new and creative. Therefore, we newly introduce Creative-GAN, which extends the original GAN framework to two discriminators, one is to determine whether it is real music, and the other is to classify music style. The paper shows that our proposed Creative-GAN can generate novel and interesting music which is not found in the training dataset. To evaluate our model, a comprehensive evaluation scheme is introduced to make subjective and objective evaluation. Compared with the advanced methods, our experimental results performs better in measureing the music rhythm, generation diversity, dance-music correlation and overall quality of generated music.