Topics include temporal coding, neural maps and feature detectors, learning and plasticity, and feedback control.
课程内容包含时间编码程序、神经系统地图与特征探测器、学习与可塑性以及回馈控制。
Firstly, the principle and implementation of temporal Scalability, spatial Scalability, SNR Coarse-grain Scalability (CGS) and SNR Fine-grain Scalability (FGS) Video Coding are introduced in detail.
首先，详细介绍了它支持的时域、空域、SNR粗粒度可分级(CGS)和SNR精细粒度可分级(FGS)编码的原理和实现；最后，对视频可分级编码技术的应用前景进行了总结。
In distributed video coding (DVC) because the decoder cannot have access to the current frame, modeling the temporal correlation noise becomes a difficult task.
在分布式视频编码(DVC)中，由于解码端不能获取当前编码帧的信息，精确地对时域相关噪声进行建模变得更为困难。
Because of considering the temporal masking effects to set up a threshold and the valid hop size of transient points, this method is very suitable for perceptual audio coding.
由于考虑了时域掩蔽效应来设置检测门限和有效瞬态点间隔，非常适用于感觉音频编码。
Scalable video coding based on MCTF (motion compensated temporal filtering) has been thought of as the important study field for it's validity of removing temporal correlation.
基于运动补偿时间滤波的可伸缩视频编码因其能有效去除时间相关性，而成为视频标准组织目前研究的热点。
Motion compensated temporal filtering is an essential component in deciding the coding performance of an interframe wavelet system.
移动补偿时间滤波是一个在决定编码的表现非常重要的要素。
The method is based on real 3d wavelet transform, and implements a three dimensional extension of SPIHT in still image coding by defining a new spatial-temporal orientation tree structure.
该方法建立在真三维小波分解基础上，通过定义一种新的时空方向树结构，实现了静止图像SPIHT算法的三维扩展。
The method is based on real 3d wavelet transform, and implements a three dimensional extension of SPIHT in still image coding by defining a new spatial-temporal orientation tree structure.
该方法建立在真三维小波分解基础上，通过定义一种新的时空方向树结构，实现了静止图像SPIHT算法的三维扩展。
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