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采樣列化的切比雪夫混沌測(cè)量矩陣構(gòu)造算法研究

發(fā)布時(shí)間:2018-07-13 15:29
【摘要】:壓縮感知利用信號(hào)的稀疏性,無損地從低維測(cè)量信號(hào)中恢復(fù)高維度稀疏信號(hào)。然而,目前存在的測(cè)量矩陣中大多存在元素相關(guān)性高等問題,無法保證恢復(fù)效果的精確性,大大制約了它們的應(yīng)用前景。針對(duì)此問題,通過引入切比雪夫混沌系統(tǒng),提出一種基于采樣列化的切比雪夫混沌感知測(cè)量矩陣(SC3M)。不同于經(jīng)典的相對(duì)獨(dú)立取值的構(gòu)造方法,SC3M矩陣通過對(duì)切比雪夫混沌序列作采樣列化及歸一化處理等操作來確保矩陣的低列相關(guān)性,以優(yōu)化重構(gòu)效果;進(jìn)一步,結(jié)合Johnson-Lindenstrauss引理嚴(yán)格證明了其滿足約束等距特性(restricted isometric property,RIP),給提出的測(cè)量矩陣的應(yīng)用提供了扎實(shí)的理論依據(jù)。實(shí)驗(yàn)仿真表明,提出的混沌測(cè)量矩陣能確保良好的信號(hào)和圖像重構(gòu)精度,明顯優(yōu)于純隨機(jī)矩陣、伯努利矩陣和高斯矩陣等其他經(jīng)典測(cè)量矩陣。
[Abstract]:Compression perception utilizes the sparsity of the signal to recover the high dimensional sparse signal from the low dimensional measurement signal. However, there are many problems in the measurement matrix, such as high correlation of elements, which can not guarantee the accuracy of the recovery effect, which greatly restricts their application prospects. To solve this problem, a Chebyshev chaotic sensing measurement matrix (SC3M) based on sampling listing is proposed by introducing Chebyshev chaotic system. In order to optimize the reconstruction effect, the SC3M matrix, which is different from the classical construction method of relatively independent values, can ensure the low column correlation of the matrix by sampling and normalizing the Chebyshev chaotic sequence. In combination with Johnson-Lindenstrauss Lemma, it is strictly proved that it satisfies the constraint isometric characteristic (restricted isometric propertyn RIP), which provides a solid theoretical basis for the application of the proposed measurement matrix. Experimental results show that the proposed chaotic measurement matrix can ensure good signal and image reconstruction accuracy, and is superior to other classical measurement matrices such as pure random matrix, Bernoulli matrix and Gao Si matrix.
【作者單位】: 廣州大學(xué)松田學(xué)院;廣東農(nóng)工商職業(yè)技術(shù)學(xué)院;中國移動(dòng)通信集團(tuán)廣東有限公司;
【基金】:廣東省省級(jí)課題資助項(xiàng)目(GDYJSKT16-08) 廣東省高等職業(yè)教育教學(xué)改革立項(xiàng)課題(201401154)
【分類號(hào)】:TN911.7

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