Training sequences

Training Sequences

Constrained Optimization of MIMO Training Sequences

Multiple-input multiple-output (MIMO) systems have shown a huge potential for increased spectral efficiency and throughput. With an increasing number of transmitting antennas comes the burden of providing training for channel estimation for coherent detection. In some special cases optimal, in the sense of mean-squared error (MSE), training sequences have been designed. However, in many practic...

The influence of visual training on predicting complex action sequences.

Linking observed and executable actions appears to be achieved by an action observation network (AON), comprising parietal, premotor, and occipitotemporal cortical regions of the human brain. AON engagement during action observation is thought to aid in effortless, efficient prediction of ongoing movements to support action understanding. Here, we investigate how the AON responds when observing...

Training with cognitive sequences improves syntactic comprehension in agrammatic aphasics.

A major open question in cognitive neuroscience concerns the modularity of language: does human language rely, in part, on neural processes that are not language specific? Such reliance would predict that learning should transfer between non-linguistic and linguistic domains via this common neural basis. To test this prediction, we studied effects of non-linguistic cognitive sequence training o...

Multiplexing VBR Video and Training Sequences on Wireless Fading Channels

A time slotted multiple access scheme that shares bandwidth between source and training signals is proposed for the transmission of variable bit rate (VBR) video signals over non-ideal channels. The error performance is examined using finite state Markov chains that model both the VBR source traffic and the time variation of fading channels. The characteristic time-scale of the fade duration, t...