A novel structure with direct inversion of a multiple input multiple output (MIMO) system is proposed in this paper. Based on this structure, 2 adaptive algorithms, LMS like and Affine projection Algorithm (APA), are ...
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A novel structure with direct inversion of a multiple input multiple output (MIMO) system is proposed in this paper. Based on this structure, 2 adaptive algorithms, LMS like and Affine projection Algorithm (APA), are proposed to directly obtain an accurate estimate of the inverse of the plant system. The proposed algorithms have faster convergence speed than the FxLMS algorithm. Furthermore, this structure does not necessitate any a prior information of plant system and it can trace the fluctuation of the plant. It is shown through simulations that the proposed method overperforms the FxLMS algorithm in convergence speed so it is much applicable to real world environments than the FxLMS algorithm.
The strong convergence properties of the projection method for convex feasibility problem are investigated in the frame of a real Hilbert space. The significant role of the regularity properties for strong convergence...
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ISBN:
(纸本)9780769530789
The strong convergence properties of the projection method for convex feasibility problem are investigated in the frame of a real Hilbert space. The significant role of the regularity properties for strong convergence of these methods is pointed out.
The theory of compressive sensing enables accurate and robust signal reconstruction from a number of measurements dictated by the signal's structure rather than its Fourier bandwidth. A key element of the theory i...
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ISBN:
(纸本)9780819468499
The theory of compressive sensing enables accurate and robust signal reconstruction from a number of measurements dictated by the signal's structure rather than its Fourier bandwidth. A key element of the theory is the role played by randomization. In particular, signals that are compressible in the time or space domain call be recovered from just a few randomly chosen Fourier coefficients. However, in some scenarios we can only observe the magnitude of the Fourier coefficients and not their phase. In this paper, we study the magnitude-only compressive sensing problem and in parallel with the existing theory derive sufficient conditions for accurate recovery. We also propose a new iterative recovery algorithm and study its performance. In the process, we develop a new algorithm for the phase retrieval problem that exploits a signal's compressibility rather than its support to recover it from Fourier transform magnitude measurements.
A novel oblique projection based detection scheme is proposed to reduce the computational cost of the vertical Bell Laboratories Layered Space-Time (V-BLAST) receivers. It constructs the ordinary zero-forcing (ZF) and...
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A novel oblique projection based detection scheme is proposed to reduce the computational cost of the vertical Bell Laboratories Layered Space-Time (V-BLAST) receivers. It constructs the ordinary zero-forcing (ZF) and minimum mean- square error (MMSE) detectors by oblique projector implementation, and has a computationally efficient way via projection matrix recursion. Different from the existing ones, we design a so-called "inverse" detection order to facilitate this new approach, whose complexity compares favorably with the competing alternatives. Theoretical analysis and simulation results show the efficiency of the proposed algorithm.
In this paper, we propose a novel adaptive filtering algorithm named adaptive parallel variable-metric projection (APVP) algorithm, which includes the proportionate normalized least mean square (PNLMS) algorithm as it...
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In this paper, we propose a novel adaptive filtering algorithm named adaptive parallel variable-metric projection (APVP) algorithm, which includes the proportionate normalized least mean square (PNLMS) algorithm as its special example. The proposed algorithm is based on parallel projection (onto multiple closed convex sets) with time-varying metrics. A convergence analysis of the proposed algorithm is presented with the aid of the adaptive projected subgradient method. Numerical examples demonstrate that the proposed algorithm realizes echo cancellation superior to the conventional algorithms.
This paper presents a novel, effective algorithm to discriminate and separate super-imposed SSR (Secondary Surveillance Radar) Mode S signals. Our goal is a blind separation of multiple SSR sources using a single chan...
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This paper presents a novel, effective algorithm to discriminate and separate super-imposed SSR (Secondary Surveillance Radar) Mode S signals. Our goal is a blind separation of multiple SSR sources using a single channel receiver. Other algorithms perform sources separation exploiting space diversity or statistical properties, but with the practical inconvenience of the need for a multi-channel receiver. As today SSR stations are equipped with single-channel receivers (for Multilateration and Wide Area Multilateration applications, M-LAT, WAM) the proposed algorithm is aimed to be operationally useful.
In this Letter, we address a novel constant modulus algorithm (CMA) based on affine projection algorithm (APA) for blind equalization transmission channel of QPSK systems to deal with inter symbol interference (ISI). ...
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In this Letter, we address a novel constant modulus algorithm (CMA) based on affine projection algorithm (APA) for blind equalization transmission channel of QPSK systems to deal with inter symbol interference (ISI). Our algorithm is more rapidly convergence, tracking properties and slightly improved steady-state equalization performance than the same category algorithms such as LMS-CMA and NLMS-CMA, and computationally more efficient with similar convergence compared with least squares algorithm (LS-CMA). Simulation results are presented to compare our APA-CMA algorithm with the blind NLMS-CMA and LS-CMA schemes.
In this paper, an image stabilization method based on the adaptive Gaussian mixture model (GMM) is presented in order to smooth down the airborne image vibration. Firstly, the projection algorithm is adopted for the m...
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ISBN:
(纸本)9781424409907
In this paper, an image stabilization method based on the adaptive Gaussian mixture model (GMM) is presented in order to smooth down the airborne image vibration. Firstly, the projection algorithm is adopted for the motion estimation;Secondly, GMM parameter is obtained after analyzing characteristics of the first n images;Finally, a stable image sequence is achieved after GMM motion filter operates on the motion parameter. The experimental results show that the method has the advantage of fast speed and effectively smooth unwanted vibration of image sequences.
This paper presents an effective algorithm to discriminate and separate superimposed SSR (secondary surveillance radar) mode S signals. The algorithm is an adaptation of the PA (projection algorithm) [1,3,4] that perf...
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This paper presents an effective algorithm to discriminate and separate superimposed SSR (secondary surveillance radar) mode S signals. The algorithm is an adaptation of the PA (projection algorithm) [1,3,4] that perform a blind separation of the multiple SSR sources using a single channel receiver. As present-days SSR stations only have a single-channel receiver, the proposed algorithm is operatively useful, specially for multilateration and wide area multilateration applications, (M-LAT, WAM). The algorithm is evaluated with real recorded data and also simulated signals generated by a complete simulation of a typical MLAT Rx station, from the RF to the digital section. We discuss as well the estimation of the time of arrival for each overlapped signal, that is necessary for the timing. Finally we propose a possible architecture for the signals separation block of the digital processor of the receiving station.
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