Aimed at the shortcoming that the loss of low-frequency information of alternating current millimeter-wave radiometer signal, relevance vector machine (RVM) algorithm is used to compensate the lost component in discre...Aimed at the shortcoming that the loss of low-frequency information of alternating current millimeter-wave radiometer signal, relevance vector machine (RVM) algorithm is used to compensate the lost component in discrete cosine transform (DCT) domain, and through inverse discrete cosine transform (IDCT) we can receive the compensated signal. RVM exploits Bayesian learning framework, which has dramatically fewer kernel functions than comparative support vector machine. So that accurate prediction models can be acquired. Experimental results also show that this method can obtain good compensation effect.展开更多
基金National Defence Foundation under Grant No.9140A05070107BQ0204
文摘Aimed at the shortcoming that the loss of low-frequency information of alternating current millimeter-wave radiometer signal, relevance vector machine (RVM) algorithm is used to compensate the lost component in discrete cosine transform (DCT) domain, and through inverse discrete cosine transform (IDCT) we can receive the compensated signal. RVM exploits Bayesian learning framework, which has dramatically fewer kernel functions than comparative support vector machine. So that accurate prediction models can be acquired. Experimental results also show that this method can obtain good compensation effect.
