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一种简单有效的基于动态时变语音识别源码
对于大多数研究者来说,寻找能够匹配二重时间序列信号的最佳途径是很重要的,因为它有许多重要的应用需求.DTW是实现这项工作的显著技术,尤其在语音识别技术领域,在这里一个测试信号被按照参照模板拉伸或压缩,
,Searching for the best path that matches two time-series signals is the main task for many researchers, because of its importa
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matlab编写的基于混沌时间序列的神经网络预测，包括一步和多步预测算法。-matlab prepared chaotic time series based on the neural network to predict, including step and multi-step prediction algorithm.
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这是《数据挖掘原理与应用—SQL Server 2008数据库》的随书SQL语句、源代码和Excel范例文件，基于DMX，代码主要包括对SQL Server 2008和Excel 2007中已经集成好的数据挖掘算法的应用， 如贝叶斯聚类、决策树、时序、聚类、序列聚类、关联规则、神经网络、逻辑回归、OLAP立方体的等算法，具有极高的使用价值。-This is the " Principles and Applications of data mining-SQL Server 2008 d
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matlab格式源代码。功能：径向基神经网络算法源码和应用于时间序列模型建立和预测问题。-matlab source code format. Function: RBF neural network algorithm source code and applies to time-series model and prediction of the problem.
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BP neural network for time series analysis predicted that by entering the corresponding time-series data to predict the future, suitable for beginners on the BP neural network learning
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Elman递归神经网络对时间序列的预测代码，做的效果还行，仅供参考-Elman recurrent neural network for time series prediction code, do the results were OK for reference purposes only
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用小波神经网络变换对时间序列信号进行预测，并做了测试，效果很好，请参考-Transform using wavelet neural network to predict the time series signal, and do a test with good results, please refer to
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基于时间序列的神经网络建模及边坡位移预测，时间序列的神经网路应用。-Neural network based on time series modeling and prediction of slope displacement, time series neural network applications.
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文章展示了一种新的方法用于功率系统中短期负载预测。提出的方案使用混沌时间序列分析基于确定性混沌去捕捉复杂的负载行为特征。确定性的混沌允许我们重构一个时间序列并决定输入的变量个数。这篇文章描述了混沌时间序列对日间功率系统峰值的分析。确定性混沌的非线性图形通过多层感知器的神经网络得到。提出的方案在一个例子中具体阐述。-This paper presents a new approach to short-term load forecasting in power systems. The
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Neural Network OCR.
There are many different approaches to optical character recognition problem. One of the most common and popular approaches is based on neural networks, which can be applied to different tasks, such as pattern recognition, time
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混沌时间序列 基于人工神经网络的一步或多步预测-Chaotic time series based on artificial neural network or multi-step prediction step
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Multi-step-prediction of chaotic time series based
on co-evolutionary recurrent neural network
协同进化递归神经网络的多步混沌时间序列预测-This paper proposes a co-evolutionary recurrent neural network (CERNN) for the multi-step-prediction of chaotic
time series, it
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采用模糊神经网络anfis预测混沌时间序列的源程序。-The source program of Using fuzzy ANFIS neural network for predicting chaotic time series.
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运用神经网络与时间序列分析对风电功率进行预测的一个matlab程序。-Using neural network and time series analysis forecast wind power
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用小波神经网络做时间序列的预测，根据前12天温度的变化预测后四天的温度-Wavelet neural network to do time series prediction, based on the temperature before and after 12 days of a four-day temperature change projections
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Time Series Forecast With Neural Network and Wavelet Techniques
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神经网络时间序列预测,采用BP网络进行的时间序列预测-Neural network time series prediction
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小波神经网络的时间序列预测-短时交通流量预测-Wavelet neural network time series prediction- Short traffic flow forecasting
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Wavelet neural network time series prediction of short-term traffic flow forecasting
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时间序列与神经网络结合，进行中国居民用电量的预测。- Combined time series and neural network for Chinese residents electricity consumption forecast.
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