本文研究基于对数域状态空间滤波器的一维连续小波变换VLSI实现理论与方法。

The theories and the methods of VLSI implementation of one-dimension continuous wavelet transform(CWT) . which bases on state-space log-domain filter, are developed in the paper.

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提出了一种基于状态空间神经网络(SSNN)和拓展卡尔曼滤波(ekf)的混合式行程时间预测模型。

This paper presents a hybrid model for urban arterial travel time prediction based on the so-called state space neural networks (SSNN) and the extended Kalman Filter (EKF).

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用M带小波变换来拟合状态在各尺度空间的投影关系，建立了满足标准卡尔曼滤波条件的系统模型。

M-band wavelet is used to approximate the projection relationship between the scale Spaces, and system model that satisfies Kalman filter condition is built.

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