组合逻辑电路的小世界网络模型

针对可编程逻辑器件中组合逻辑电路的优化设计问题,依据复杂网络理论中小世界模型分簇的基本特征,提出了双重优化设计指标下的电路设计方法,以16位奇偶校验电路为例,利用Matlab对电路进行了仿真。仿真结果表明,通过适当降低网络分簇度,有效削弱关键节点在电路中的作用,并适当增加网络连接的冗余性,避免关键元器件的故障导致整个系统的灾害性失败的现象出现,从而降低电路的脆弱性,提高电路鲁棒性和可靠性。

A novel scale-free network model based on clique growth

A novel scale-flee network model based on clique （complete subgraph of random size） growth and preferential attachment was proposed. The simulations of this model were carried out. And the necessity of two evolving mechanisms of the model was verified. According to the mean-field theory, the degree distribution of this model was analyzed and computed. The degree distribution function of vertices of the generating network P（d） is 2m^2m1^-3（d-m1 ＋ 1）^-3, where m and m1 denote the number of the new adding edges and the vertex number of the cliques respectively, d is the degree of the vertex, while one of cliques P（k） is 2m^2Ek^-3, where k is the degree of the clique. The simulated and analytical results show that both the degree distributions of vertices and cliques follow the scale-flee power-law distribution. The scale-free property of this model disappears in the absence of any one of the evolving mechanisms. Moreover, the randomicity of this model increases with the increment of the vertex number of the cliques.

Preparation of Ultrafine SiO2 Powder from Rice Husk and Properties of Its Infrared Spectrum

This paper discussed impact of temperature on the size distribution in preparing ultrafine silica from rice husk.The samples prepared were analyzed with infrared spectrum,and the relation between the particle size and intensity of characteristic absorption peak of IR at center around 1 100 cm-1 was disscussed with the baseline method.Results show that when the temperature is 650 ℃ and roasting time is 11 h,at optimal reaction conditions,the size distribution of the ultrafine silica powder prepared is relatively concentrated,and the average particle size is 199.5 nm.Moreover,the characteristic absorption band of IR is broadening gradually along with particle size decreasing.

Local porosity distribution of cement paste characterized by X-ray micro-tomography

Porosity is one of the most important parameters for cement-based materials,which influences the mechanical property,transport property,and durability.The spatial and frequency distributions of local porosity of cement pastes are characterized using X-ray micro-tomography data and treating methods.The 3D spatial distributions for three cement paste specimens with different water cement(w/c)ratios show reasonable heterogeneity.The probability analysis also reveals this heterogeneity:the representative volume element(RVE)size based on porosity maps decreases with w/c ratio firstly,then increases with w/c ratio;and the heterogeneity on the characterized probe size or on the RVE size increases with w/c ratio.Average porosities obtained using the CT method are further compared with those by traditional methods.

Classification of hyperspectral remote sensing images using frequency spectrum similarity

An algorithm of hyperspectral remote sensing images classification is proposed based on the frequency spectrum of spectral signature.The spectral signature of each pixel in the hyperspectral image is taken as a discrete signal,and the frequency spectrum is obtained using discrete Fourier transform.The discrepancy of frequency spectrum between ground objects' spectral signatures is visible,thus the difference between frequency spectra of reference and target spectral signature is used to measure the spectral similarity.Canberra distance is introduced to increase the contribution from higher frequency components.Then,the number of harmonics involved in the proposed algorithm is determined after analyzing the frequency spectrum energy cumulative distribution function of ground object.In order to evaluate the performance of the proposed algorithm,two hyperspectral remote sensing images are adopted as experimental data.The proposed algorithm is compared with spectral angle mapper (SAM),spectral information divergence (SID) and Euclidean distance (ED) using the product accuracy,user accuracy,overall accuracy,average accuracy and Kappa coefficient.The results show that the proposed algorithm can be applied to hyperspectral image classification effectively.