单调递增函数

This paper gives a concept of Lebesgue-Stieltjes measure in monotone increasing left continuous bounded function and discuss some properties.

以单调递增左连续有界函数 f 给出了 Lebesgue-Stieltjes测度的概念，进一步讨论了由它产生的若干相应的性

Properties of efficient portfolios and the efficient frontier to the model are systematically analyzed. Our main results concerning the properties are: every efficient portfolio can be solved by minimizing portfolio risk under a given level of portfolio return or by maximizing portfolio return under a given level of portfolio risk; on the efficient frontier, the risk is a convex and strictly increasing function of the return and the return is a concave and strictly increasing function of the risk; the utility function on the efficient frontier can be expressed as a quasi-concave function of the risk or the return if the investor's utility function is quasi-concave.

从理论上系统地对该模型下的有效投资组合和有效前沿的性质进行了分析，结果表明：每一个有效投资组合可通过在给定期望收益水平的条件下最小化投资组合风险来获得，或者在给定风险水平的条件下最大化期望投资组合收益来获得；在有效前沿上，风险是收益的严格单调递增凸函数，收益是风险的严格单调递增凹函数；当投资者的效用函数是拟凹函数时，则有效前沿上的效用可表达成风险或收益的拟凹函数。

In the proof,sufficient conditions are proved mainly by properties of K function and continuity of Lyapunov function:in necessary proof,we separately structure Lyapunov functions which satisfy the conditions of the theorems, such that the results establish.

在定理的证明中充分性主要利用K类函数严格单调递增和Lyapunov函数的连续性；必要性的证明中，分别构造Lyapunov函数，满足定理的条件，使得定理的结论成立。

W ithout assuming the boundedness, monotonicity, differentiability and Lipschitz continuity of the active functions, an algebraic criterion to ensure existence and globally exponential stability of periodic solutions was obtained.

在 放松该类神经网络激活函数的有界性、单调递增性、可微性及Lipschitz连续等条件下，得到了该类神经网络周期解的存在性与全局指数稳定的代数判据。

These networks are generalized without assuming the boundedness, monotonicity and differenciability of the activate functions.

在放松神经网络的激活函数的有界性、单调递增性和可微性的条件下，得到了神经网络的全局渐近稳定的条件。

In chapter 2, we firstly introduce the model of a discrete-time neural network with generalized input-output function. The model generalizes the input-output function in transiently chaotic neural network to a class of continuous, differentiable and monotone increasing functions. Secondly we study the uniformly asymptotical stability of equilibrium in the non-autonomous model. Finally, several examples and numerical simulations are given to illustrate and reinforce our theories. In chapter 3, we firstly introduce a specific class of discrete-time neural network models with sinusoidal activation function.

在本文的第二章中，首先介绍了一类具有广义输入输出函数的非自治离散神经网络模型，该模型把瞬时混沌神经网络模型中的输入输出函数推广到了一般的单调递增且连续可微的函数；其次，利用Schauder不动点原理和利用Lyapunov函数逆定理依次证明了模型平衡点的存在性和该模型在时变权值下的一致渐近稳定性；最后，对几个具体的例子进行数值模拟，数值模拟的结果更好地说明了我们的结论。

The model generalizes the input-output function in transiently chaotic neural network to a class of continuous, differentiable and monotone increasing functions. Secondly we study the uniformly asymptotical stability of equilibrium in the non-autonomous model. Finally, several examples and numerical simulations are given to illustrate and reinforce our theories. In chapter 3, we firstly introduce a specific class of discrete-time neural network models with sinusoidal activation function.

在本文的第二章中，首先介绍了一类具有广义输入输出函数的非自治离散神经网络模型，该模型把瞬时混沌神经网络模型中的输入输出函数推广到了一般的单调递增且连续可微的函数；其次，利用Schauder不动点原理和利用Lyapunov函数逆定理依次证明了模型平衡点的存在性和在时变权值下的一致渐近稳定性；最后，对几个具体的例子进行数值模拟，数值模拟的结果更好地说明了我们的结论。

For situations of self-rational agents, Inter-Multi-Agent-Contract was formulated to describe the negotiation status of distributed planning and scheduling. Monotonously increasing voidance and violence penalties were defined to facilitate reciprocal cooperation. Negotiation protocol was designed based on bidding and bargaining theory. Commitment mechanism that permits non-immediately effective commitments and enforces monotonously increasing voidance penalty was defined to promote the efficiency of negotiation.

在个体理性条件下的分布计划和调度问题研究中，定义了多代理间合约来描述协商状态，提出通过单调递增的失效和违约惩罚机制来促进代理间的互利协作；基于投标、讨价还价理论建立了合约协商协议，提出通过非即时生效和失效函数单调递增的承诺机制来提高合约协商效率；针对问题域的时间限制定义了协商停止问题，提出了若干解决上述问题的方法。

According to the monotonically increasing match criteria around the location of the optimal motion vector a fast fractional motion estimation algorithm based on the group error is presented.

根据匹配准则的目标函数在最优运动矢量的附近都是单调递增这一假设，提出一种基于分组误差的快速分数像素运动估计算法。

Singer Leona Lewis and former Led Zeppelin guitarist Jimmy Page emerged as the bus transformed into a grass-covered carnival float, and the pair combined for a rendition of "Whole Lotta Love".

歌手leona刘易斯和前率领的飞艇的吉他手吉米页出现巴士转化为基层所涵盖的嘉年华花车，和一双合并为一移交&整个lotta爱&。

This is Kate, and that's Erin.

这是凯特，那个是爱朗。