无线电引信多普勒信号增速器的研究

论述了无线电引信多普勒信号增速器的实现原理及意义，介绍了采用ＴＭＳ３２０Ｃ３０作为ＣＰＵ、多片大容量静态ＲＡＭ芯片构成海量存储体的信号增速器硬件结构和软件设计，并提出了今后的研究方向。     

Distributed memory systems for simulating artificial neural networks

In executing tasks involving intelligent information processing, the human brain performs better than the digital computer. The human brain derives its power from a large number [O(10¹¹)] of neurons which are interconnected by a dense interconnection network [O(10⁵) connections per neuron]. Artificial neural network (ANN) paradigms adopt the structure of the brain to try to emulate the intelligent information processing methods of the brain. ANN techniques are being employed to solve problems in areas such as pattern recognition, and robotic processing. Simulation of ANNs involves implementation of large number of neurons and a massive interconnection network. In this paper, we discuss various simulation models of ANNs and their implementation on distributed memory systems. Our investigations reveal that communication-efficient networks of distributed memory systems perform better than other topologies in implementing ANNs.     

微机对调制信号的包络解调

应用检相原理，可以提取有限长度调制信号和包络解调。通过改变Ａ／Ｄ转换器的位数，提高检相分辨率，它与检测对象的速度无关。这为提高检相分辨率展示了新的途径。     

Drugs, memory, and metamemory: A dose-effect study with lorazepam and scopolamine.

This experiment was designed to use the graded dose-related amnesia produced by the benzodiazepine lorazepam (1.0, 2.0 mg/70 kg, oral) and the anticholinergic scopolamine (0.3, 0.6 mg/70 kg, subcutaneous) as a tool to explore the cognitive and neurochemical mechanisms underlying metamemory in the judgment of learning paradigm, with a placebo-controlled independent groups design in healthy volunteers (n=12/group). Results provide evidence for a pharmacological dissociation between effects on memory versus metamemory (relative accuracy of item-by-item monitoring) across a range of levels of memory performance and suggest that the drugs selectively impair those aspects of metamnemonic monitoring that require participants' awareness of their overall current state of functioning (absolute accuracy of prospective item-by-item monitoring, prospective global monitoring) but not those that rely solely on assessment of individual item characteristics (relative accuracy of item-by-item monitoring). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Putting it all together – Formal verification of the VAMP

In the verified architecture microprocessor (VAMP) project we have designed, functionally verified, and synthesized a processor with full DLX instruction set, delayed branch, Tomasulo scheduler, maskable nested precise interrupts, pipelined fully IEEE compatible dual precision floating point unit with variable latency, and separate instruction and data caches. The verification has been carried out in the theorem proving system PVS. The processor has been implemented on a Xilinx FPGA. A shorter version of this article with the title “Instantiating uninterpreted functional units and memory system: functional verification of the VAMP” appeared in [8]. The work reported here was done while all the authors were with Saarland University.     

A hierarchical model for structure learning based on the physiological characteristics of neurons

Almost all applications of Artificial Neural Networks (ANNs) depend mainly on their memory ability. The characteristics of typical ANN models are fixed connections, with evolved weights, globalized representations, and globalized optimizations, all based on a mathematical approach. This makes those models to be deficient in robustness, efficiency of learning, capacity, anti-jamming between training sets, and correlativity of samples, etc. In this paper, we attempt to address these problems by adopting the characteristics of biological neurons in morphology and signal processing. A hierarchical neural network was designed and realized to implement structure learning and representations based on connected structures. The basic characteristics of this model are localized and random connections, field limitations of neuron fan-in and fan-out, dynamic behavior of neurons, and samples represented through different sub-circuits of neurons specialized into different response patterns. At the end of this paper, some important aspects of error correction, capacity, learning efficiency, and soundness of structural representation are analyzed theoretically. This paper has demonstrated the feasibility and advantages of structure learning and representation. This model can serve as a fundamental element of cognitive systems such as perception and associative memory.     

Absolute Measurements of the Magnetic Field Generated by Different Coils in the Center of EGYPTOR Tokamak

The present work is devoted to measure the absolute magnetic field produced by different coils in the EGYPTOR tokamak using a calibrated pickup coil. Scaling these measurements in different equations connected with the discharge currents from each supply system are performed. The pickup coil used in the present study is well calibrated with Helmholz coils at the IPP in Prague, Czech Republic. A 0.2% deviation has been found between an evaluation done in the present study and the calibration using Helmholz coils. Experimental measurements of the toroidal magnetic field are in good agreement with calculations to within 2%. Very low values of stray magnetic field components arising from TF and OH coils are recorded which proves that the compensation coils for these components are sufficient.     

Improvement of levitation characteristics in a magnetic bearing system using HTSC‐permanent magnet hybrid structure

Magnetic bearing using pinning force of a permanent magnet and a high‐temperature superconductor has been developed. Additional permanent magnet is introduced to increase the levitation force of the magnetic bearing. In this hybrid magnetic bearing system, levitation force is mainly given by the repulsive force of the permanent magnets, and stability for the lateral direction is given by pinning force of the superconductor. The experimental device is developed. A ring‐type superconductor and a bulk one are examined. Levitation characteristics of the hybrid magnetic bearing are measured. The bulk superconductor shows better characteristics of both levitation and lateral stability than the ring one. Levitation force of the hybrid system becomes about twice as large as that of the nonhybrid one. Although, the repulsive force of the permanent magnet decreases the lateral stability of the system, its influence becomes small by choosing an adequate position of the permanent magnets and the superconductor. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(1): 71–77, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10350     

The mirror effect and mixture signal detection theory.

The mirror effect for word frequency refers to the finding that low-frequency words have higher hit rates and lower false alarm rates than high-frequency words. This result is typically interpreted in terms of conventional signal detection theory (SDT), in which case it indicates that the order of the underlying old item distributions mirrors the order of the new item distributions. However, when viewed in terms of a mixture version of SDT, the order of hits and false alarms does not necessarily imply the same order in the underlying distributions because of possible effects of mixing. A reversal in underlying distributions did not appear for fits of mixture SDT models to data from 4 experiments. (PsycINFO Database Record (c) 2010 APA, all rights reserved)