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.     

Voltage transfer function synthesis using current conveyors

A synthesis procedure for generating current conveyor active filters is presented, and a novel network which realises the general 2nd-order voltage transfer function is given.<>     

吸入短寿命氡子体动物肺组织剂量与体重关系的探讨

本文介绍吸入短寿命氡子体的不同种动物肺组织吸收剂量与体重的关系。实验结果表明,吸收剂量随体重的增加而减小。     

巯基棉预浓集—中子活化法测定水泥及其浸出水中的微量汞

在不同酸度下巯基棉可以从溶液中富集和分离Au、As、Ag、Br、Cu、Ca Co、InHg、Ni、Se、Sb、Sn、Pb、W、Fe和In等30多种元素。由于用巯基棉吸附待测元素后不必洗脱,因此大大提高了富集能力,可用于海水、地下水、地表水及工业废水中一些元素的测量。本文用巯基棉富集后进行中子活化分析测定水泥及其浸出水中的汞。     

A 16-Mbit/s adapter chip for the IBM token-ring local area network

The authors describe a 9.02×9.02-mm chip built in 1-μm CMOS with two levels of metal and an additional mask level for fabricating capacitors. It contains both analog and digital circuits and has provisions for self-test. The function includes the transmitter, receiver, protocol handler, an microprocessor, as well as interfaces for RAM/ROM storage, IBM PC bus, IBM PS/2 bus, IBM 3174 bus, and Motorola 68000 bus. The physical design terrains are formed by 24K circuits of standard cell gates, a 10K-circuit equivalent hand-honed custom microprocessor, and an analog macro. The chip operates from a single 5-V supply, and the power consumption is 0.8 W nominal at 16 Mb/s. The chip can also be operated at 4 Mb/s     

A New Modified Gaussian Approximation Detector for Space-Time Bit-Interleaved Coded Modulation Schemes

To reduce the receiver complexity of the space-time bit-interleaved coded modulation (ST-BICM) scheme, this letter describes a turbo-type iterative structure consisting of a modified Gaussian approximation (MGA) detector and an a posteriori probability (APP) decoder. Utilizing the characteristics of the interleaving and the central limited theoretic, the MGA detector first assumes the superposition of the transmitted signals as a Gaussian random variable. Then, P most significant signal combinations are identified to calculate the log-likelihood ratio of each bit. Without any pre-process on the received signals, the proposed method is free of matrix inverse operation and can be applied in systems with more transmit antennas than receive antennas. Furthermore, the performance of the MGA approaches that of the optimal detection