利用DSP底层结构提高MPEG-4编码的实时性

由于利用TMS320C6000系列的DSP底层结构可以提高图像压缩的实时性,本文在TMS320C6416平台上针对DSP底层结构对MPEG-4视频编码进行了优化,包括对8个运算单元能并行执行的特性进行汇编。针对DSP芯片两级高速缓存的工作特点,对编码器中代码和数据所占用的内存空间进行优化。利用EDMA级联特性在内存开辟双缓冲区,同时完成视频数据编码和传输的工作,从而有效地改善编码效率。实验结果表明：该编码器可以对512 pixel×512 pixel大小的灰度图像,以30 frame/s帧频进行压缩,实现了对视频图像的实时编码。     

Analytical Approach for Piecewise Linear Coupled Map Lattices

A simple construction is presented which generalizes piecewise linear one-dimensional Markov maps to an arbitrary number of dimensions. The corresponding coupled map lattice, known as a simplicial mapping in the mathematical literature, allows for an analytical investigation. In particular, the spin Hamiltonian which is generated by the symbolic dynamics is accessible. As an example, a formal relation between a globally coupled system and an Ising mean-field model is established. The phase transition in the limit of infinite system size is analyzed and analytical results are compared with numerical simulations.     

Matlab软件在三线摆法测定圆环转动惯量中的应用

使用三线摆可以测量圆环的转动惯量,但测量的物理量较多,人工处理数据比较繁琐,且容易出错。因此,本文使用Matlab软件处理数据。把测量的实验数据输入Excel表格中,引入Matlab软件中运行相关程序后可以直接得到圆环的转动惯量,以及测量的百分差和相对不确定度,处理过程快捷精确。     

神光-Ⅲ主机黑腔腔形研究与设计

利用三维视角因子软件IRAD3D研究了神光-Ⅲ主机靶丸表面辐射驱动时变对称性和驱动强度随黑腔腔形和排布方式的变化。模拟结果表明:采用椭球形黑腔能显著减小黑腔壁面积从而减小腔壁能量消耗并提高靶丸消耗份额;不同腔形和排布方式下均可通过调节腔长使勒让德不对称性模P2时间积分量较小;采用双环辐照和椭球腔形都利于缩短腔长;四环排布利于调节P4分量,但环向不对称性M4较差;椭球腔双环排布能兼顾极向不对称性P2,P4和环向不对称性M4,且靶丸表面X光驱动强度相对柱腔双环提高25%~27%。     

Recent progress of computational investigation on anode materials in Li ion batteries

Computations have been widely used to explore new Li ion battery materials because of its remarkable advantages. In this review, we summarize the recent progress on computational investigation on anode materials in Li ion batteries. By introducing the computational studies on Li storage capability in carbon nanotubes, graphene, alloys and oxides, we reveal that computations have successfully addressed many fundamental problems and are powerful tools to understand and design new anode materials for Li ion batteries.     

Performance of a four‐element Si drift detector for X‐ray absorption fine‐structure spectroscopy: resolution, maximum count rate,and dead‐time correction with incorporation into the ATHENA data analysis software

The performance of a four‐element Si drift detector for energy‐dispersive fluorescence‐yield X‐ray absorption fine‐structure measurements is reported, operating at the National Institute of Standards and Technology beamline X23A2 at the National Synchrotron Light Source. The detector can acquire X‐ray absorption fine‐structure spectra with a throughput exceeding 4 × 10⁵ counts per second per detector element (>1.6 × 10⁶ total counts per second summed over all four channels). At this count rate the resolution at 6 keV is approximately 220 eV, which adequately resolves the Mn Kα and Kβ fluorescence lines. Accurate dead‐time correction is demonstrated, and it has been incorporated into the ATHENA data analysis program. To maintain counting efficiency and high signal to background, it is suggested that the incoming count rate should not exceed ～70% of the maximum throughput.     

Ion-trap quantum information processing:experimental status

Atomic ions trapped in ultra-high vacuum form an especially well-understood and useful physical system for quantum information processing. They provide excellent shielding of quantum information from environmental noise, while strong, well-controlled laser interactions readily provide quantum logic gates. A number of basic quantum information protocols have been demonstrated with trapped ions. Much current work aims at the construction of large-scale ion-trap quantum computers using complex microfabricated trap arrays. Several groups are also actively pursuing quantum interfacing of trapped ions with photons.      

Analog computation through high-dimensional physical chaotic neuro-dynamics

Conventional von Neumann computers have difficulty in solving complex and ill-posed real-world problems. However, living organisms often face such problems in real life, and must quickly obtain suitable solutions through physical, dynamical, and collective computations involving vast assemblies of neurons. These highly parallel computations through high-dimensional dynamics (computation through dynamics) are completely different from the numerical computations on von Neumann computers (computation through algorithms). In this paper, we explore a novel computational mechanism with high-dimensional physical chaotic neuro-dynamics. We physically constructed two hardware prototypes using analog chaotic-neuron integrated circuits. These systems combine analog computations with chaotic neuro-dynamics and digital computation through algorithms. We used quadratic assignment problems (QAPs) as benchmarks. The first prototype utilizes an analog chaotic neural network with 800-dimensional dynamics. An external algorithm constructs a solution for a QAP using the internal dynamics of the network. In the second system, 300-dimensional analog chaotic neuro-dynamics drive a tabu-search algorithm. We demonstrate experimentally that both systems efficiently solve QAPs through physical chaotic dynamics. We also qualitatively analyze the underlying mechanism of the highly parallel and collective analog computations by observing global and local dynamics. Furthermore, we introduce spatial and temporal mutual information to quantitatively evaluate the system dynamics. The experimental results confirm the validity and efficiency of the proposed computational paradigm with the physical analog chaotic neuro-dynamics.