噪声理论能解释我国封闭式基金折价交易现象吗——与薛刚、顾锋、黄培清三位先生商榷

封闭式证券投资基金折价交易作为一种普遍现象在西方受到深入的研究 ,因为其意义不仅在于解释为什么会存在折价 ,更重要是在于为捍卫或批判有效市场假说提供了检验的场所 ;同时也为验证到底有无“噪声交易者”提供了一个好机会。本文以在上海证券交易所交易的基金为样本对我国封闭式证券投资基金折价交易现象进行实证分析 ,验证了广为接受的“投资者情绪假说”不能解释我国封闭式基金的折价交易问题。同时提出并验证这一现象可能与投资者在不同时期对基金的偏好有关。

Application and optimization design of non-obstructive particle damping-phononic crystal vibration isolator in viaduct structure-borne noise reduction

The problems associated with vibrations of viaducts and low-frequency structural noise radiation caused by train excitation continue to increase in importance.A new floating-slab track vibration isolator-non-obstructive particle damping-phononic crystal vibration isolator is proposed herein,which uses the particle damping vibration absorption technology and bandgap vibration control theory.The vibration reduction performance of the NOPD-PCVI was analyzed from the perspective of vibration control.The paper explores the structure-borne noise reduction performance of the NOPD-PCVIs installed on different bridge structures under varying service conditions encountered in practical engineering applications.The load transferred to the bridge is obtained from a coupled train-FST-bridge analytical model considering the different structural parameters of bridges.The vibration responses are obtained using the finite element method,while the structural noise radiation is simulated using the frequency-domain boundary element method.Using the particle swarm optimization algorithm,the parameters of the NOPD-PCVI are optimized so that its frequency bandgap matches the dominant bridge structural noise frequency range.The noise reduction performance of the NOPD-PCVIs is compared to the steel-spring isolation under different service conditions.

高校德育工作的复杂性探析

高校德育是一个"人为的"和"为人的"复杂系统。复杂性科学以"超越还原论"为旗帜,借助于混沌性、整体性、非线性和组织性等思维方式为高校德育工作的创新提供了一种全新的视角。在复杂性科学的视阈下,高校德育工作的创新应体现在更新教育理念、彰显受教育者的主体地位、关注"噪声"的意义以及建构一个"开放性"的德育内容体系等方面。

Galvanic corrosion behavior of copper/titanium galvanic couple in artificial seawater

The corrosion behaviors of copper and copper/titanium galvanic couple （GC） in seawater were studied by electrochemical impedance spectroscopy （EIS） and electrochemical noise （EN） techniques in conjunction with scanning electron microscopy （SEM） method. The results show that the corrosion process of copper in seawater can be divided into two stages, in which corrosion resistance and SE show the same evolution trend of initial increase and subsequent decrease, while SG changes oppositely. However, the ensemble corrosion process of copper/titanium GC in seawater includes three stages, in which corrosion resistance and SE show the evolution features of initial decrease with a subsequently increase, and the final decrease again;while SG changes oppositely. The potential difference between copper and titanium in their galvanic couple can accelerate the initiation of pitting corrosion of copper, and both the minimum and maximum corrosion potentials of copper/titanium GC are much more positive than those of pure copper.

Effect of Weak Noise on the Frequency Tuning of Mouse Inferior Collicular Neurons

In order to study the effect of weak noise on the sound signal extraction of mouse (Mus musculus Km) inferior collicular (IC) neurons from environments,we examined the changes in frequency tuning curves (FTCs) of 32 neurons induced by a weak noise relative to 5 dB below minimum threshold of tone (reMT-5 dB) under free field stimulation conditions.The results were as follows:① There were three types of variations in FTCs,sharpened (34.4%),broadened (18.8%),and unaffected (46.9%),nevertheless,only the alteration of sharpened FTCs was statistically different.② Sharpness of frequency tuning induced by a reMT-5 dB noise was very strong.Q 10 and Q 30 of FTCs were increased by (34.42±17.04)% (P=0.026,n=11) and (46.34±22.88)% (P=0.009,n=7).③ The changes of inverse-slopes (ISs,kHz/dB) between high (IS high) and low (IS low) limbs of FTCs were dissymmetry.The IS high of FTCs decreased markedly (P=0.046,n=7),however,there was little change (P=0.947,n=7) in IS low.Our data revealed for the first time that the weak noise could sharpen frequency tuning and increase the sensitivity on the high frequency of sound signal in IC neurons of mouse.

Engine Noise Source Identification with Different Methods

Engine noise source identification is essential for making noise reduction strategies.Predominant noise sources of engines are normally identified as some cover components such as oil pan, valve cover and front gear cover etc. The radiated noise sources of a 6-cylinder construction diesel engine are identified with two methods-lead covering technique and surface vibration technique,and the ranking of the major cover on the basis of acoustic power is presented in this paper. Firstly the sound power level of these cover components and their contributions to the total acoustic power are determined with lead covering method under hemi-anechoic condition. Then the vibration characteristics of these components are investigated. The sound power level of various components is predicted via the mean square area average vibration. Both results basically agree well and verify the effectiveness of both techniques in engineering field.

Seismic random noise suppression using an adaptive nonlocal means algorithm

Nonlocal means filtering is a noise attenuation method based on redundancies in image information. It is also a nonlocal denoising method that uses the self-similarity of an image, assuming that the valid structures of the image have a certain degree of repeatability that the random noise lacks. In this paper, we use nonlocal means filtering in seismic random noise suppression. To overcome the problems caused by expensive computational costs and improper filter parameters, this paper proposes a block-wise implementation of the nonlocal means method with adaptive filter parameter estimation. Tests with synthetic data and real 2D post-stack seismic data demonstrate that the proposed algorithm better preserves valid seismic information and has a higher accuracy when compared with traditional seismic denoising methods （e.g., f-x deconvolution）, which is important for subsequent seismic processing and interpretation.

Signal extraction for GPS deformation monitoring in mining survey

The basic signal model of deformation monitoring with GPS was introduced and the main problems of GPS deformation monitoring in mining area were discussed. For the problem of noise signal extraction in GPS deformation monitoring, the Kalman-EMD method was proposed to obtain the effective deformation signal. The reliability and effectiveness of the methodology were tested and verified by analog signal. The results of experiment in Mongolia show that the accuracy of the proposed GPS deformation monitoring model is equivalent to that of level method.

Implementation of a 6 GHz band TDD RF transceiver for the next generation mobile communication system

The development of a high performance wideband radio frequency （RF） transceiver used in the next generation mobile communication system is presented. The developed RF transceiver operates in the 6 to 6.3 GHz band and the channel bandwidth is up to 100 MHz. It operates in the time division duplex （TDD） mode and supports the multiple-input multipleoutput （MIMO） technique for the international mobile telecommunications （IMT）-advanced systems. The classical superheterodyne scheme is employed to achieve optimal performance. Design issues of the essential components such as low noise amplifier, power amplifier and local oscillators are described in detail. Measurement results show that the maximum linear output power of the RF transceiver is above 23 dBm, and the gain and noise figure of the low noise amplifier is around 24 dB and below 1 dB, respectively. Furthermore, the error vector magnitude （EVM） measurement shows that the performance of the developed RF transceiver is well beyond the requirements of the long term evolution （LTE）-advanced system. With up to 8 x 8 MIMO configuration, the RF transceiver supports more than a 1 Gbit/s data rate in field tests.

An iterative curvelet thresholding algorithm for seismic random noise attenuation

In this paper,we explore the use of iterative curvelet thresholding for seismic random noise attenuation.A new method for combining the curvelet transform with iterative thresholding to suppress random noise is demonstrated and the issue is described as a linear inverse optimal problem using the L1 norm.Random noise suppression in seismic data is transformed into an L1 norm optimization problem based on the curvelet sparsity transform. Compared to the conventional methods such as median filter algorithm,FX deconvolution, and wavelet thresholding,the results of synthetic and field data processing show that the iterative curvelet thresholding proposed in this paper can sufficiently improve signal to noise radio（SNR） and give higher signal fidelity at the same time.Furthermore,to make better use of the curvelet transform such as multiple scales and multiple directions,we control the curvelet direction of the result after iterative curvelet thresholding to further improve the SNR.

Random noise attenuation by f–x spatial projection-based complex empirical mode decomposition predictive filtering

The frequency–space（f–x） empirical mode decomposition（EMD） denoising method has two limitations when applied to nonstationary seismic data. First, subtracting the first intrinsic mode function（IMF） results in signal damage and limited denoising. Second, decomposing the real and imaginary parts of complex data may lead to inconsistent decomposition numbers. Thus, we propose a new method named f–x spatial projection-based complex empirical mode decomposition（CEMD） prediction filtering. The proposed approach directly decomposes complex seismic data into a series of complex IMFs（CIMFs） using the spatial projection-based CEMD algorithm and then applies f–x predictive filtering to the stationary CIMFs to improve the signal-to-noise ratio. Synthetic and real data examples were used to demonstrate the performance of the new method in random noise attenuation and seismic signal preservation.

A low-phase-noise and low-power crystal oscillator for RF tuner

A 37. 5 MHz differential complementary metal oxide semiconductor （CMOS） crystal oscillator with low power and low phase noise for the radio frequency tuner of digital radio broadcasting digital radio mondiale （DRAM） and digital audio broadcasting （DAB） systems is realized and characterized. The conventional cross-coupled n-type metal oxide semiconductor （NMOS） transistors are replaced by p-type metal oxide semiconductor （PMOS） transistors to decrease the phase noise in the core part of the crystal oscillator. A symmetry structure of the current mirror is adopted to increase the stability of direct current. The amplitude detecting circuit made up of a single- stage CMOS operational transconductance amplifier （OTA） and a simple amplitude detector is used to improve the current accuracy of the output signals. The chip is fabricated in a 0. 18- pxn CMOS process, and the total chip size is 0. 35 mm x 0. 3 mm. Under a supply voltage of 1.8 V, the measured power consumption is 3.6 mW including the output buffer for 50 testing loads. The proposed crystal oscillator exhibits a low phase noise of - 134. 7 dBc/Hz at 1-kHz offset from the center frequency of 37. 5 MHz.

Seismic data denoising based on mixed time-frequency methods

Deconvolution denoising in the f-x domain has some defects when facing situations like complicated geology structure, coherent noise of steep dip angles, and uneven spatial sampling. To solve these problems, a new filtering method is proposed, which uses the generalized S transform which has good time-frequency concentration criterion to transform seismic data from the time-space to time-frequency-space domain （t-f-x）. Then in the t-f-x domain apply Empirical Mode Decomposition （EMD） on each frequency slice and clear the Intrinsic Mode Functions （IMFs） that noise dominates to suppress coherent and random noise. The model study shows that the high frequency component in the first IMF represents mainly noise, so clearing the first IMF can suppress noise. The EMD filtering method in the t-f-x domain after generalized S transform is equivalent to self-adaptive f-k filtering that depends on position, frequency, and truncation characteristics of high wave numbers. This filtering method takes local data time-frequency characteristic into consideration and is easy to perform. Compared with AR predictive filtering, the component that this method filters is highly localized and contains relatively fewer low wave numbers and the filter result does not show over-smoothing effects. Real data processing proves that the EMD filtering method in the t-f-x domain after generalized S transform can effectively suppress random and coherent noise of steep dips.

A normalized wavefield separation cross-correlation imaging condition for reverse time migration based on Poynting vector

Prestack reverse time migration（PSTM） is a common imaging method; however low-frequency noises reduce the structural imaging precision. Thus, the suppression of migration noises must be considered. The generation mechanism of low-frequency noises is analyzed and the up-, down-, left-, and right-going waves are separated using the Poynting vector of the acoustic wave equation. The computational complexity and memory capacitance of the proposed method are far smaller than that required when using the conventional separation algorithm of 2D Fourier transform. The normalized wavefield separation crosscorrelation imaging condition is used to suppress low-frequency noises in reverse time migration and improve the imaging precision. Numerical experiments using the Marmousi model are performed and the results show that the up-, down-, left-, and right-going waves are well separated in the continuation of the wavefield using the Poynting vector. We compared the imaging results with the conventional method, Laplacian filtering, and wavefield separation with the 2D Fourier transform. The comparison shows that the migration noises are well suppressed using the normalized wavefield separation cross-correlation imaging condition and higher precision imaging results are obtained.

Seismic dip estimation based on the twodimensional Hilbert transform and its application in random noise attenuation

In seismic data processing, random noise seriously affects the seismic data quality and subsequently the interpretation. This study aims to increase the signal-to-noise ratio by suppressing random noise and improve the accuracy of seismic data interpretation without losing useful information. Hence, we propose a structure-oriented polynomial fitting filter. At the core of structure-oriented filtering is the characterization of the structural trend and the realization of nonstationary filtering. First, we analyze the relation of the frequency response between two-dimensional（2D） derivatives and the 2D Hilbert transform. Then, we derive the noniterative seismic local dip operator using the 2D Hilbert transform to obtain the structural trend. Second, we select polynomial fitting as the nonstationary filtering method and expand the application range of the nonstationary polynomial fitting. Finally, we apply variableamplitude polynomial fitting along the direction of the dip to improve the adaptive structureoriented filtering. Model and field seismic data show that the proposed method suppresses the seismic noise while protecting structural information.

A Ka Broadband High Gain Monolithic LNA with a Noise Figure of 2dB

A four-stage monolithic microwave integrated circuits （MMIC） low noise amplifier （LNA） operating from 23 to 36GHz is reported using commercially available 0.15μm PHEMT technology. The LNA is self-biased. To achieve a low noise characteristic, careful optimizations of gate width are performed to reduce gate resistance. Absorption circuits and an elaborate bias structure with a resistor-capacitor network are employed to improve stability. Multiple resonance points and negative feedback technologies are used to widen the bandwidth. Measurements show a noise figure （NF） of less than 2.0dB,and the lowest NF is only 1.6dB at a frequency of 31GHz. In the whole operation band,the LNA has a gain of higher than 26dB,and an input return loss and output return loss of more than 11 and 13dB,respectively. The output power at ldB compression gain of 36GHz is about 14dBm. The chip area is 2.4mm ×1mm.

Mixed noise removal for color images using quaternion representation

In order to effectively restore color noisy images with the mixture of Gaussian noise and impulse noise,a new algorithm is proposed using the quaternion-based holistic processing idea for color images.First,a color image is represented by a pure quaternion matrix.Secondly,according to the different characteristics of the Gaussian noise and the impulse noise,an algorithm based on quaternion directional vector order statistics is used to detect the impulse noise. Finally,the quaternion optimal weights non-local means filter （QOWNLMF）for Gaussian noise removal is improved for the mixed noise removal.The detected impulse noise pixels are not considered in the calculation of weights.Experimental results on five standard images demonstrate that the proposed algorithm performs better than the commonly used robust outlyingness ratio-nonlocal means （ROR-NLM）algorithm and the optimal weights mixed filter （OWMF）.

Characterization of pitting corrosion of 7A60 aluminum alloy by EN and EIS techniques

The pitting corrosion behaviors of 7A60 aluminum alloy in the retrogression and re-aging （RRA） temper were investigated by electrochemical impedance spectroscopy （EIS） and electrochemical noise （EN） techniques, and the microstructure and the second phase content of the alloy were observed and determined by scanning electron microscopy （SEM） and energy dispersive spectrometer （EDS）. The results show that there exist two different corrosion stages for 7A60 alloy in 3.5%NaCl solution, and the corrosion process can be detected by the appearance of EIS spectrum with two capacitive time constants and the wavelet fractal dimension D extracted from EN. SEM and EDS results also demonstrate that severe pitting corrosion in 7A60 alloy is mainly caused by electrochemical active MgZn2 particles, secondly by Al2MgCu and Mg2Si. Al7Cu2Fe particles make little contribution to the pitting corrosion of 7A60 alloy.

A seafloor electromagnetic receiver for marine magnetotellurics and marine controlled-source electromagnetic sounding

In planning and executing marine controlled-source electromagnetic methods, seafloor electromagnetic receivers must overcome the problems of noise, clock drift, and power consumption. To design a receiver that performs well and overcomes the abovementioned problems, we performed forward modeling of the E-field abnormal response and established the receiver＇s characteristics. We describe the design optimization and the properties of each component, that is, low-noise induction coil sensor, low-noise Ag/AgCI electrode, low-noise chopper amplifier, digital temperature-compensated crystal oscillator module, acoustic telemetry modem, and burn wire system. Finally, we discuss the results of onshore and offshore field tests to show the effectiveness of the developed seafloor electromagnetic receiver and its performance： typical E-field noise of 0.12 nV/m/rt（Hz） at 0.5 Hz, dynamic range higher than 120 dB, clock drift lower than 1 ms/day, and continuous operation of at least 21 days.