This article proposes a novel fixed-frequency beam scanning leakage antenna based on a liquid crystal metamaterial (LCM) and adopting a metal column embedded microstrip line (MCML) transmission structure. Based on the microstrip line (ML) transmission structure, it was observed that by adding two rows of metal columns in the dielectric substrate, electromagnetic waves can be more effectively transmitted to reduce dissipation, and attenuation loss can be lowered to improve energy radiation efficiency. This antenna couples TEM mode electromagnetic waves into free space by periodically arranging 72 complementary split ring resonators (CSRRs). The LC layer is encapsulated in the transmission medium between the ML and the metal grounding plate. The simulation results show that the antenna can achieve a 106° continuous beam turning from reverse −52° to forward 54° at a frequency of 38 GHz with the holographic principle. In practical applications, beam scanning is achieved by applying a DC bias voltage to the LC layer to adjust the LC dielectric constant. We designed a sector-blocking bias feeder structure to minimize the impact of RF signals on the DC source and avoid the effect of DC bias on antenna radiation. Further comparative experiments revealed that the bias feeder can significantly diminish the influence between the two sources, thereby reducing the impact of bias voltage introduced by LC layer feeding on antenna performance. Compared with existing approaches, the antenna array simultaneously combines the advantages of high frequency band, high gain, wide beam scanning range, and low loss.
In order to improve the invisibility of watermark information, this paper proposes a technique of embedding watermark according to the direction of digital colorful image texture.First, the scrambling watermarking Image is obtained by chaotic scrambling and Fast Fourier Transformation (FFT).Second, the embedding channel of the colorful carrier image is chosen which depends on human visual characteristics and PSNR, and Gray Level Co-occurrence Matrix is applied to judge the direction which is suitable for the Dual-Tree Complex Wavelet Transformation (DTCWT) decomposition directions ( 15 , 45 , 75 ) .Third, the chosen channel is DTCWT decomposed into the third level, the sub-image which is suitable for the direction is substituted by the scrambling watermarking Image.In the end, the decomposed carrier image is inverse Dual-Tree Complex Wavelet transformed to obtain the watermarked image.In the extraction procession, the conjugate image generated by FFT is corrected by inverse chaotic scrambling.Results: Experimental results show that the algorithm can well embed the watermark into the colorful image, and the invisibility of the watermarking image is better in the image area with the texture direction.
A new fast high-order neural network learning algorithm for pattern recognition is proposed. The new learning algorithm uses some properties of trigonometry for reducing and controlling the number of weights of a third-order network used for invariant pattern recognition. Experimental results on typed upper case English letters indicate that the new approach maintains the higher classification accuracy and reduces the complexity of neural networks significantly. The proposed method can also be adapted for applications in some other pattern recognition problems.
The problem of state estimation with quantised measurements is considered for general vector state-vector observation model in wireless sensor networks (WSNs), which broadens the scope of sign of innovations Kalman filtering (SOI-KF) and multiple-level quantised innovations Kalman filter (MLQIKF). Adhering to the limited power and bandwidth resources WSNs must operate with, this paper introduces a novel decentralised unscented Kalman filtering (UKF) estimators based on quantised measurement innovations. In the quantisation approach, the region of a measurement innovation is partitioned into L contiguous, non-overlapping intervals. After quantised, the measurement information is broadcasted by using a variable number of bytes coding method. A filtering algorithm for general vector state-vector observation case is developed based on the quantised measurement information. Performance analysis and Monte Carlo simulations reveal that under the same bandwidth constraint condition, the performance of novel quantised UKF tracker, indeed better than those of SOI-KF and MLQIKF in error covariance matrix (ECM) and root mean-square error (RMSE) and almost identical to these of an UKF based on analogue-amplitude observations.
In the process of watermark embedding and extraction, there is a great contradiction between the invisibility and robustness of the watermark.In order to solve this contradiction, this paper presents a semiblind watermarking algorithm for printing image anti-counterfeiting in CMYK space, based on Arnold scrambling, 2D-DCT and dual-tree complex wavelet transform (DT-CWT).First, Arnold Scrambling is applied to the watermark image.Then the scrambled watermark image is transformed by 2D-DCT to obtain the frequency domain image.Second, the obtained frequency domain image is used to replace the sub-band containing the least information in the wavelet coefficient tree obtained from DT-CWT of the carrier CMYK image, and then applying invers dual-tree complex wavelet transform to the decomposed wavelet coefficient tree to get the watermarked CMYK image.The extraction process uses module matching technology to perform optimal watermark extraction on the watermarked images.Experimental results show that the algorithm not only has good confidentiality, but also can resist various attacks such as cropping, rotation, filtering, noise addition, lossy compression, etc.It is very suitable for anti-counterfeiting authentication of printed products.
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