Proportional-type NLMS algorithm with gain allocation providing maximum one-step conditional PDF for true weights

机译：具有增益分配的比例式NLMS算法为真实权重提供最大的一步式条件PDF

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In this paper, we present a proportionate-type normalized least mean square algorithm which operates by choosing adaptive gains at each time step in a manner designed to maximize the conditional probability that the next-step coefficient estimates reach their optimal values. We compare and show that the performance of the maximum conditional probability density one-step algorithm is superior to the normalized least mean square algorithm and the proportionate normalized least mean square algorithm. Additionally, we argue that the algorithm we present operates for any impulse response.

机译：在本文中，我们提出了一种比例类型的归一化最小均方算法，该算法通过选择每个时间步长的自适应增益来进行操作，该算法旨在最大程度地提高下一步系数估计达到其最佳值的条件概率。我们进行比较并显示，最大条件概率密度单步算法的性能优于归一化最小均方算法和比例归一化最小均方算法。此外，我们认为我们提出的算法可用于任何冲激响应。

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来源
《Information Sciences and Systems, 2009. CISS 2009》|2009年|61-66|共6页
会议地点 Baltimore MD(US);Baltimore MD(US);Baltimore MD(US)
作者
Wagner K.T.; Doroslovacki M.I.;
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Radar Div., Naval Res. Lab., Washington, DC;

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关键词
adaptive filters; least squares approximations; optimisation; probability; transient response; adaptive filter; adaptive gain allocation; constrained optimization; impulse response; maximum one-step conditional PDF; normalized least mean square algorithm; probability density function; proportional-type NLMS algorithm; true weight;

机译：自适应滤波器;最小二乘近似;优化;概率;瞬态响应;自适应滤波器;自适应增益分配;约束优化;脉冲响应;最大单步条件PDF;归一化最小均方算法;概率密度函数;比例式NLMS算法;真实重量;

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4. Proportional-type NLMS Algorithm with Gain Allocation Providing Maximum One-step Conditional PDF for True Weights [C] . Kevin T. Wagner, Milos I. Doroslovacki Annual Conference on Information Sciences and Systems . 2009

机译：具有增益分配的比例型NLMS算法为真正权重提供最大一步条件PDF
5. Feasibility and acceptability of regular weighing setting weight gain limits and providing feedback by community midwives to prevent excess weight gain during pregnancy: randomised controlled trial and qualitative study [O] . AJ Daley, K. Jolly, SA Jebb, 2015

机译：定期称重的可行性和可接受性设定体重增加限制并由社区助产士提供反馈以防止怀孕期间体重增加：随机对照试验和定性研究
6. Feasibility and acceptability of regular weighing, setting weight gain limits and providing feedback by community midwives to prevent excess weight gain during pregnancy: randomised controlled trial and qualitative study [O] . AJ Daley, K. Jolly, SA Jebb, 2015

机译：定期称重的可行性和可接受性，设定体重增加限制并由社区助产士提供反馈以防止怀孕期间体重增加：随机对照试验和定性研究
7. Gain Allocation in Proportionate-Type NLMS Algorithms for Fast Decay of Output Error at All Times [R] . Wagner, K. T., Doroslovacki, M. I. 2009

机译：比例型NLms算法中的增益分配，用于随时快速衰减输出误差

Proportional-type NLMS algorithm with gain allocation providing maximum one-step conditional PDF for true weights

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