Advanced Materials Research Vols. 926-930

Abstract: Compressive sensing is a new type of digital signal processing method. The novel objective of compressive Sensing is to reconstruct a signal accurately and efficiently from far fewer sampling points got by Nyquist sampling theorem. Compressive sensing theory combines the process of sampling and compression to reduce the complexity of signal processing, which is widely used in many fields. so there are wide application prospects in the areas of radar image, wireless sensor network (WSN), radio frequency communication, medical image processing, image device collecting and so on. One of the important tasks in CS is how to recover the signals more accurately and effectively, which is concerned by many researchers. Compressive sensing started late; there are many problems and research directions worthy of our in-depth research. At present, many researchers shove focused on reconstruction algorithms. Reconstruction algorithms are the core of compressive sensing, which are of great significance to reconstructing compressed signals and verifying the accuracy in sampling. These papers introduce CosaMP algorithm; and then study and analyze the Gaussian noise as the main content. Finally, the given signal and random signal, for example, we give a series of comparison results.

Abstract: For locally linear embedding (LLE) algorithm of the shortcoming, an improved distance algorithm LLE is proposed, in locally linear embedding algorithm the distribution of sample component is different and the Euclidean distance can’t reflect sample distance actually. In the experiment, a sample of 231 neurons is obtained, and the morphological parameters of neurons are calculated firstly. Second, the improved locally linear embedding algorithm is used to reduce data dimensionality. Finally, support vector machine (SVM) algorithm is used to train and test samples. Experimental results show under certain conditions the classification of the method has good classification.

Abstract: This paper presents an improvement fast image interpolation algorithm, which we divided the low resolution images into smooth area, edge area and texture area based on threshold control mode, then we using three channel to achieve fast interpolation. Experiments show that this method makes the image texture details clear, won the high resolution image.

Abstract: The sparsity rating data is one of the main challenges of recommendation system. For this problem, we presented a collaborative filtering recommendation algorithm integrated into co-ratings impact factor. The method reduced the sparsity of rating matrix by filling the original rating matrix. It made the full use of rating information and took the impact on similarity of co-ratings between users into consideration when looking for the nearest neighbor so that the similarities were accurately computed. Experimental results showed that the proposed algorithm, to some extent, improved the recommendation accuracy.

Abstract: Currently, most researchers select clustering-based algorithms to generate the initial training set for active learning. Considering that for such algorithms, a single clustering is not stable, we propose an initial training set selection algorithm which combines multi-clustering results to select samples. Specifically, after each clustering, it delimits several representative regions. If a sample falls into its corresponding representative region, then the algorithm casts a vote for it to mark that it is a potential representative sample. Finally, after several clustering, the samples with the most votes are selected. Experimental results show that our algorithm can efficiently select the informative samples, and can make the classifier have a more stable performance.

Abstract: As an important part of food safety, the safety of food packaging receives increasingly attention from public. Some chemicals in the food container or packaging would migration after contacting with food for a long time. We analyze three classical plasticizer migration models in China, and give contrast analysis. Then we measured the antioxidants migration status under different circumstances, getting the original experimental data. In addition, we adopt the best experiment scheme among the three methods, measuring the migration of antioxidants in different situations and obtain migration curves.

Abstract: The article talks about the history of animation, focusing on the production of computer-assisted animation effects. Include key technologies of early modeling animation, motion control, distribution plan and other colors. Tracking the most advanced animation techniques and methods. Finally, introduce the application of the major animation techniques.

Abstract: This paper presents the designing and realization of a Ka-band 4th sub-harmonic image rejection mixer using anti-parallel diode pair (APDP). Measured performance is as follow: RF:29.4~31GHz, IF is 100MHz, Conversion loss is11.2~12.3dB and image rejection is larger than 20.2dB with the LO power 11dBm and RF power-30dBm. Both RF-IF isolation and LO-IF isolation are larger than 34.4dB.

Abstract: This paper presents a component of unified processing for remote sensing image files based on GDAL. The component, which developed an interface specification for unified remote sensing image processing, encapsulates processing operations of remote sensing image files to form an integral, such as GeoTIFF, HDF, SHP, etc.. The component effectively achieves a variety format image files to read and write, save, display, and conversion, to facilitate the development and application of remote sensing image processing system, and reduce the cost of software development.

Abstract: The key and difficult issue in the research of binocular vision-based 3D measurement is the accurate calibration of internal and external parameters of the camera and stereo matching. Matlab calibration is more efficient and accurate compared with manual or OpenCV calibration. In this paper, binocular camera is calibrated by Matlab calibration toolbox, and calibration parameters imported in OpenCV for follow-up image correction and stereo matching. By studying and comparing Block Matching (BM) and Graph Cut (GC) stereo matching algorithms, a disparity image of the object is obtained, thus laying foundation for follow-up 3D data information acquisition and reconstruction.