换个角度看复利计息公式

本文从微分方程出发 ,导出了连续复计息情景下的资金增长方程 ,为该方程的建立提供了一个新视角 ,揭示了三个资金增长方程的内在联系。

邮储管理漏洞多 亟待改进和规范

邮政储蓄业务自开办以来,在为国家回笼货币,聚集资金,增加中央银行宏观调控能力等方面发挥了积极的作用。同时,邮政储蓄业务本身也得到了较快发展,截止1995年末,我省邮政储蓄网点达到1151个,从业人员3789人,储蓄余额103.5亿元,实现利差收入2.6亿元。据调查。

国家鼓励企业兼并的优惠政策

国家鼓励优势企业兼并困难企业,兼并企业要全部承担被兼并企业的债务并负责人员安排,被兼并企业的富余人员也要实行下岗分流,在此基础上,根据有关文件规定精神,被兼并企业银行债务可享受免除利息、分年还本的优惠。优势企业(包括国有控股企业)兼并连续3年亏损的企业,经银行核准,可免除被兼并企业原欠贷款利息;被兼并企业原欠贷款本金分5年还清,如5年内还本仍有困难,可给予1～2年的宽限期。

MP-WFRFT and Constellation Scrambling Based Physical Layer Security System

In this paper, a multiple parameters weighted fractional Fourier transform(MPWFRFT) and constellation scrambling(CS) method based physical layer(PHY) security system is proposed. The proposed scheme is executed by two steps. In the first step, MPWFRFT, implemented as the constellation beguiling(CB) method, is applied to change the signal's identity. In the second step the additional pseudo random phase information, regarded as the encryption key, is attached to the original signal to enhance the security. Typically, the pseudo random phase information can be removed effectively by the legitimate receiver. In contrast to the cryptography based encryption algorithms and the conventional PHY secrecy techniques, the main contribution of the proposed scheme is concentrated on the variation in signal's characteristics. Simulation results show that the proposed scheme can prevent the exchanging signal from eavesdroppers' classifi cation or inception. Moreover, the proposed scheme can guarantee the BER performance at a tolerate increasing in computational complexity for the legitimate receivers.

Efficient Recovery of Structured Sparse Signals via Approximate Message Passing with Structured Spike and Slab Prior

Due to limited volume, weight and power consumption, micro-satellite has to reduce data transmission and storage capacity by image compression when performs earth observation missions. However, the quality of images may be unsatisfied. This paper considers the problem of recovering sparse signals by exploiting their unknown sparsity pattern. To model structured sparsity, the prior correlation of the support is encoded by imposing a transformed Gaussian process on the spike and slab probabilities. Then, an efficient approximate message-passing algorithm with structured spike and slab prior is derived for posterior inference, which, combined with a fast direct method, reduces the computational complexity significantly. Further, a unified scheme is developed to learn the hyperparameters using expectation maximization(EM) and Bethe free energy optimization. Simulation results on both synthetic and real data demonstrate the superiority of the proposed algorithm.

Relaying Strategy Based on Estimated Information for Multi-Antenna Cooperative Networks

A sphere-based list forwarding scheme for multiple-input multiple-output(MIMO) relay networks is proposed and analyzed. Firstly, an estimate forwarding(EF) method is proposed, which forwards the minimum mean squared error(MMSE) estimate of the source data to the destination. Since it performs like amplify-and-forward(AF) and decode-and-forward(DF) for the low and high signal-to-noise ratio(SNR) regions, respectively, the EF relay thus outperforms conventional AF and DF across all SNRs without the need for switching algorithms for different SNRs. Because computational complexity is however high for relays with a large number of antennas(large MIMO) and/or high order constellations, list EF for large MIMO relay networks is proposed. It computes a list sphere decoder based MMSE estimate and retains the advantages of the exact EF relay at a negligible performance loss. The proposed list EF could offer a flexible trade-off between the performance and computational complexity.

Wireless Channel Parameter Estimation Algorithms: Recent Advances and Future Challenges

Temporal and three-dimensional(3 D) spatial information is important for the characterization of wireless channels. In this paper, the commonly used array signal processing(ASP) methods to estimate channel parameters are summarized. Firstly, algorithms that can be used to estimate azimuth angle of arrival(AAo A) and elevation Ao A(EAo A) are introduced. They include multiple signal classification(MUSIC), estimation of signal parameter via rotational invariance techniques(ESPRIT), and Unitary ESPRIT algorithms. Secondly, algorithms that can be used to jointly estimate delay, AAo A, and EAo A are given. They include joint angle and delay estimation(JADE) MUSIC, JADE ESPRIT, shift-invariance(SI) JADE, and space-alternating generalized expectation-maximization(SAGE) algorithms. We also propose an improved SIJADE algorithm to further reduce computation complexity by incorporating with the Unitary ESPRIT algorithm. Performance of the above algorithms to extract only spatial information and to jointly extract temporal and spatial information is compared in both synthetic and 60 GHz real channel environments. Simulation results show that with the inclusion of delay estimation, the joint temporal and spatial estimation algorithms can provide better resolution than algorithms estimating only angles.Measurement data processing results show that MUSIC algorithm can provide comparable results with SAGE algorithm in estimating AAoA and EAoA. SI-JADE and the improved SI-JADE algorithms are also applicable to process 60 GHz channel measurement data.However, MUSIC, SI-JADE, and the improved SI-JADE algorithms can greatly reduce computational burden compared with SAGE algorithm. At last, some future directions are pointed out.

Dynamical Criticality:Overview and Open Questions

Systems that exhibit complex behaviours are often found in a particular dynamical con- dition, poised between order and disorder. This observation is at the core of the so-called criticality hypothesis, which states that systems in a dynamical regime between order and disorder attain the highest level of computational capabilities and achieve an optimal trade-off between robustness and flexibility. Recent results in cellular and evolutionary biology, ueuroscience and computer science have revitalised the interest in the criticality hypothesis, emphasising its role as a viable candidate general law in adaptive complex systems. This paper provides an overview of the works on dynamical criticality that are -- To the best of our knowledge -- Particularly relevant for the criticality hypothesis. The authors review the main contributions concerning dynamics and information processing at the edge of chaos, and illustrate the main achievements in the study of critical dynamics in biological systems. Finally, the authors discuss open questions and propose an agenda for future work.