• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.1012-1015
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• 2011

The decision-directed blind equalization algorithm is often used due to its simplicity and good convergence property when the eye pattern is open. However, in a channel where the eye pattern is closed, the decision-directed algorithm is not guaranteed to converge. Hence, a modified Bussgang-type algorithm using a hyperbolic tangent function for zero-memory nonlinear(ZNL) function has been proposed and applied to avoid this problem by Filho et al. But application of this algorithm includes the calculation of hyperbolic tangent function and its derivative or a look-up table which may need a large amount of memory due to channel variations. To reduce the computational and/or hardware complexity of Filho's algorithm, in this paper, an improved method for the decision-directed algorithm is proposed. In the proposed scheme, the ZNL function and its derivative are respectively set to be the original signum function and a narrow rectangular pulse which is an approximation of Dirac delta function. It is shown that the proposed scheme, when it is combined with decision-directed algorithm, reduces the computational complexity drastically while it retains the convergence and steady-state performance of the Filho's algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.2
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• pp.338-344
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• 1994

Price`s theorem is generalized for general zero memory nonlinear function when input are drawn from a sum, called the constrained non-Gaussian, of two or more mutually independent processes of which the first is the Gaussian. An example is given to illustrate the applicability of the generalization.

• ETRI Journal
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• v.35 no.4
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• pp.644-654
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• 2013

In this paper, a signal detection scheme for cognitive radio (CR) based on the Bussgang theorem is proposed. The proposed scheme calculates the statistical difference between Gaussian noise and the primary user signal by applying the Bussgang theorem to the received signal. Therefore, the proposed scheme overcomes the noise uncertainty and gives scalable complexity according to the zero-memory nonlinear function for a mobile device. We also present the theoretical analysis on the detection threshold and the detection performance in the additive white Gaussian noise channel. The proposed detection scheme is evaluated by computer simulations based on the IEEE 802.22 standard for the wireless regional area network. Our results show that the proposed scheme is robust to the noise uncertainty and works well in a very low signal-to-noise ratio.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.80-87
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• 2015

Memristor is a new kind of memory device whose resistance varies depending upon applied charge and whose previous resistance state is preserved even when its power is off. Ordinary memristor has a nonlinear programming characteristics about time when a constant voltage is applied. For the easiness of programming, it is desirable that resistance is programmed linearly about time. We had proposed previously a memristor bridge configuration with which weight can be programmed nicely in positive, negative or zero. In memristor bridge circuit, two memristors are connected in series with different polarity. Memristors are complementary each other and it follows that the memristance variation is linear with respect to time. In this paper, the linearization effect of weight programming of memristor bridge synapse is investigated and verified about both $TiO_2$ memristor from HP and a nonlinear memristor with a window function. Memristor bridge circuit would be helpful to conduct synaptic weight programming.