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Exact performance analyses over correlated $\alpha$-$\mu$ fading channels result in intractable multifold integrals or infinite series. In this paper, upper and lower bounds are derived for outage probabilities and error rates of maximum-ratio combining (MRC), selection combining (SC), and equal-gain combining (EGC) over the $\alpha$-$\mu$ fading channels with arbitrary correlation. The derived...
In this paper, we investigate the performance of a dual-hop amplify-and-forward (AF) relay system with beamforming (BF), where the source and destination are both equipped with multi-antenna, which are correlated in space, while the relay has a single antenna corrupted by multiple co-channel interferences (CCIs). We first derive the closed-form expression for the outage probability (OP) of the output...
To improve the mean acquisition time performance of the zero-padding (ZP) method, we propose to fully exploit the computation capability of FFT by partially folding the local pseudo-noise (PN) code. The detection and mean acquisition time performance of the proposed method is analyzed and compared with that of the zero-padding method. It is shown that the proposed method can reduce the mean acquisition...
This paper presents a design procedure using the correlation-based identification to determine the compensation coefficients. A method for verifying the compensation coefficients is also proposed. That solved the open-loop frequency response of digitally controlled switched-mode power supply is difficult to accurately measure and provided a method to test the function of digital compensators. Experimental...
By analyzing the acquisition data of the wind turbine, we calculate the correlation dimension of the vibration signals, and take it as the feature parameter which typifies the working state of blades. The calculation results indicated that the correlation dimension is effective to reflect the dynamic structure of chaotic attractor. Thus the correlation dimension of blades' vibration signals can be...
In this paper, we restudy the non-convex data factorization problems (regularized or not, unsupervised or supervised), where the optimization is confined in the nonnegative orthant, and provide a unified convergency provable solution based on multiplicative nonnegative update rules. This solution is general for optimization problems with block-wisely quadratic objective functions, and thus direct...
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