Xieting Ling

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Conventional blind signal separation algorithms do not adopt any asymmetric information of the input sources, thus the convergence point of a single output is always unpredictable. However, in most of the applications, we are usually interested in only one or two of the source signals and prior information is almost always available. In this paper, a(More)
In this paper, we develop a wavelet collocation method with nonlinear companding for behavioral modeling of analog circuits. To construct the behavioral models, the circuit is first partitioned into building blocks and the input-output function of each block is then approximated by wavelets. As the blocks are mathematically represented by sets of simple(More)
The Autocorrelation Matching method is a blind signal separation and channel equalization technique for distributed MIMO communication systems over unknown FIR channels using only second order statistics. This method is based on a theoretical discovery, i.e., under the condition that the autocorrelation functions of the (multiple) inputs are linearly(More)
In this paper, a novel wavelet balance method is proposed for steady-state analysis of nonlinear circuits. The proposed method presents several merits compared with those conventional frequency domain techniques. First, it has a high convergence rate. Second, it works in time domain so that many critical problems in frequency domain can be handled(More)
Based on a new diversity, the diversity of autocorrelation, a new multiplex-access scheme, called A-CDMA, is presented here. Like WCDMA, it packs high-density information into transmitted signals. Unlike WCDMA, it can block all the ISI and MAI completely under all noise level! The simulation supports the theory and shows that the total interference due to(More)