Efficient Terahertz Plasmonic Absorbers with V-Grooves Using Highly Doped Silicon Substrate and Simple Wet-Etching Techniques

We experimentally demonstrate that at terahertz frequencies perfect plasmonic absorbers made from a 3D V-groove array in a highly doped silicon wafer can be easily realized using simple wet-etching process. The surface plasmon modes can be excited by the V-groove array and get decayed when they propagate along the silicon surface and enter the grooves, inducing a broadband near-zero dip in the reflection spectra. The reflection spectrum of the fabricated absorber is characterized using a terahertz time-domain spectroscopy system, and the experimental results are in good agreement with numerical simulations. The high performance including high absorptivity and large bandwidth together with the easy fabrication processes presented in this paper make this plasmonic absorber promising for a wide range of practical applications in terahertz regime.     

A Study of PN Junction Diffusion Capacitance of MOSFET in Presence of Single Event Transient

In this paper, a 65 nm MOSFET 3D structure is built based on Technology Computer Aided Design (TCAD) 3D device simulation software, and the single-event transient (SET) effect in 65 nm CMOS inverter is analyzed using TCAD-HSPICE mixed-mode simulation based on heavy ion model. The formation and function of the PN junction diffusion capacitance in the Metal-Oxide-Semiconductor (MOS) device are discussed by analyzing the drain and substrate voltage characteristics of the device under the SET effect. Then the sub-circuit structure of this device for SET is established, and the mechanism of the diffusion capacitance of PN junction during the heavy ion action process is verified comparing with the results of sub-circuit HSPICE simulation results and the TCAD-HSPICE simulation results. Finally, A sub-circuit model is provided, to support circuit-level simulation of single-event effects.     

A new direction-of-arrival estimation method exploiting signal structure information

A new method is proposed to estimate the direction-of-arrival (DOA) based on uniform linear array sampling and named as sparsity and temporal correlation exploiting (SaTC-E). By exploiting the structure information of source signals, including spatial sparsity and temporal correlation of sources, SaTC-E accomplishes DOA estimation with superior performance via block sparse bayesian learning methodology and grid refined strategy. SaTC-E is applicable into time-varying manifold scenario, such as wideband sources, time-varying array, provided that the array manifold matrix is determinable. It has improved performance with some other merits, including superior resolution, requirement for a few snapshots, no knowledge of source number, and applicability to spatially and temporally corrected sources. Real data tests and numerical simulations are carried out to demonstrate the advantages of SaTC-E.     

EXIF-white balance recognition for image forensic analysis

Due to the lack of post-processing resistance, traditional forensic methods are vulnerable to cascade image manipulations, e.g. copy-and-paste operation followed by high compression. Different from these traditional methods, a new forensic method that has the ability to resist multiple types of post-processing, is proposed by using white balance from the EXchangeable Image File format (EXIF) header. We first extract image quality metrics between each two combination of one original image and twelve re-balanced images. By regularizing the eigen spectrum of image quality metrics, the compact set of image eigen features is then selected for recognizing different EXIF-white balance modes via the SVM classifier. The experimental results show that the proposed method has the ability to resist the influence of high compression or heavy downsampling in both theoretical and realistic scenarios. Furthermore, thanks to image eigen features affected by cascade image operations, it is possible to lead to a wrong white balance mode. Thus, we use the EXIF-white balance parameter as a manipulator indicator for forgery detection. Based on the forgery photos in practice, the proposed evidence can detect cascade manipulated images which are subject to copy-and-paste followed by different white balance post-processing operations, high compression or heavy downsampling.     

Sum and difference coarray based MIMO radar array optimization with its application for DOA estimation

Based on the sum and difference coarrays, multiple-input multiple-output (MIMO) radar with minimum redundancy (MR) concept, referred to as MR MIMO, can considerably increase the spatial degrees of freedom (DOFs). However, traditional MR MIMO needs computational search to determine the position of each element. In this paper, a modified MR monostatic MIMO configuration is proposed, referred to as MMRM MIMO. In the proposed system, the MMRM MIMO radar is consisted of several levels of uniform linear array, which brings the advantage that the position of each element can be determined without computational search. Furthermore, it offers more than \(N^{2}\) DOFs for an N-elemental array. In order to utilize the extended DOFs of MMRM MIMO radar for direction-of-arrival (DOA) estimation, an average Toeplitz approximation method (TAM) is employed, which achieves robust performance even under low signal-to-noise ratio, few snapshots and array error. Numerous simulation results are provided to demonstrate the effectiveness of the proposed method for DOA estimation.     

Robotic grasping recognition using multi-modal deep extreme learning machine

Recognizing which part of an object is graspable or not is important for intelligent robot to perform some complicated tasks. In order to obtain good grasping performance, learning rich representations efficiently from multi-modal RGB-D images is crucial. To address this problem, in this paper, we propose an effective multi-modal deep extreme learning machine structure. In this structure, unsupervised hierarchical extreme learning machine (ELM) is conducted for feature extraction for RGB and depth modalities separately. Then, the shared layer is developed by combining both RGB and depth features. Finally, the ELM is used as supervised feature classifier for final decision. Experimental validation on Cornell grasping dataset illustrates that the proposed multiple modality fusion method achieves better grasp recognition performance.     

An overview of spectrum sensing techniques for cognitive LTE and LTE-A radio systems

Advanced communication systems, such as long term evolution (LTE) and LTE-advanced (LTE-A) systems, promise to increase the number of users with high-speed data exchange. However, it leads to spectrum scarcity because of the huge size of data exchange with limited spectrum resources. Cognitive radio (CR) technique is considered the best solution for this spectrum scarcity problem. Spectrum sensing (SS), one of the CR techniques is used to detect the spectrum hole of primary user (PU) without interference with PU. In this paper, several SS approaches for LTE and LTE-A systems are investigated in the CR system. These SS approaches are based on two techniques, namely energy detection and cyclostationary feature detection techniques. The first technique includes four approaches of auto-correlation based advanced energy, time domain detection, Welch periodogram and two-stage model algorithms, while the second technique contains two approaches, namely pilot induced cyclostationary and second order cyclostationary algorithms. According to the analysis, the two-stage model and the second order cyclostationary algorithms are better than the other algorithms because they produce accurate results at the expense of system complexity. Hence, in general a good SS algorithms would require some trade-off between complexity and accuracy.     

Design of different planar geometries of antenna arrays for isoflux radiation in GEO satellites

The synthesis of different planar geometries of antenna arrays for isoflux radiation is presented in this paper. This synthesis considers the reduction of the side lobe level and the isoflux radiation requirements for Geostationary Earth Orbit satellites. The behavior of the radiation is studied in three geometries of two-dimensional antenna arrays such as uniform planar arrays, aperiodic planar arrays (APA) and concentric ring arrays (CRA). The well-known methods of genetic algorithm and particle swarm optimization are utilized for the optimization problem. In this way, the designs of APA and CRA presented in this paper could provide an acceptable solution for reducing the antenna hardware and simplifying the power feeding even more than results presented previously in the literature.     

Packet dispatching using module matching in the modified MSM Clos-network switch

A modified memory-space-memory (MSM) Clos-network switch, called MCNS, with a module-level matching packet dispatching scheme, is presented in the paper. The MCNS is a modification of the MSM Clos-network switch proposed to simplify the packet dispatching scheme. In this paper, we evaluate the combinatorial properties of the MCNS, as well as a new module-level matching packet dispatching algorithm. We also show how this algorithm can be implemented in an field-programmable gate array chip. Selected simulation results obtained for the MCNS are compared with the results obtained for the MSM Clos-network switch using other module-level matching algorithms.