• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.396-401
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• 2006

It is well-known that a neural network with cyclic connections generates plural limit cycles, thus, being used as a memory system for storing large number of dynamic information. In this paper, a continuous-time cyclic connection neural network was built so that each neuron is connected only to its nearest neurons with binary synaptic weights of ${\pm}1$. The type and the number of limit cycles generated by such network has also been demonstrated through simulation. In particular, the effect of chaos signal for transition between limit cycles has been tested. Furthermore, it is evaluated whether the chaotic noise is more effective than random noise in the process of the dynamical neural networks.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.159-165
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• 1994

In this paper, we propose a multi-layer associative neural network structure suitable for hardware implementaion with the function of performance refinement and improved robutst capability. Unlike other methods which reduce network complexity by putting restrictions on synaptic weithts, we are imposing a requirement of hidden layer neurons for the function. The proposed network has synaptic weights obtainted by Hebbian rule between adjacent layer's memory patterns such as Kosko's BAM. This network can be extended to arbitary multi-layer network trainable with Genetic algorithm for getting hidden layer memory patterns starting with initial random binary patterns. Learning is done to minimize newly defined network error. The newly defined error is composed of the errors at input, hidden, and output layers. After learning, we have bidirectional recall process for performance improvement of the network with one-shot recall. Experimental results carried out on pattern recognition problems demonstrate its performace according to the parameter which represets relative significance of the hidden layer error over the sum of input and output layer errors, show that the proposed model has much better performance than that of Kosko's bidirectional associative memory (BAM), and show the performance increment due to the bidirectionality in recall process.

• Fibers and Polymers
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• v.4 no.4
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• pp.188-194
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• 2003

Phase behavior and spinodal phase separation kinetics in binary blends of a random copolymer of vinylidene fluoride and trifluoroethylene (75/25) [P(VDF/TrFE)] and poly(l,4-butylene adipate) (PBA) have been investigated by means of optical microscopic observation and time-resolved light scattering. The blends exhibited a typical lower critical solution temperature (LCST)∼${34}^{\circ}C$ above the melting temperature of the P(VDF/TrFE) crystals over the entire blend composition range. P(VDF/TrFE) and PBA were totally miscible in the temperature gap between the melting point of P(VDF/TrFE) and the LCST. Temperature jump experiments of the 3/7 P(VDF/TrFE)/PBA blend were carried out on a light-scattering apparatus from a single-phase melt state (${180}^{\circ}C$) to a two-phase region (205∼${215}^{\circ}C$). Since the late stage of spinodal decomposition (SD) is prevalent in the 3/7 blend, SD was analyzed using a power law scheme. Self-similarity was preserved well in the late stage of SD in the 3/7 blend.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.965-980
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• 2011

In this paper, the use of conditional Fuzzy C-Means (CFCM) aimed at estimation of desired states of an unknown digital communication channel is investigated for blind channel equalization. In the proposed CFCM, a collection of clustered centers is treated as a set of pre-defined desired channel states, and used to extract channel output states. By considering the combinations of the extracted channel output states, all possible sets of desired channel states are constructed. The set of desired states characterized by the maximal value of the Bayesian fitness function is subsequently selected for the next fuzzy clustering epoch. This modification of CFCM makes it possible to search for the optimal desired channel states of an unknown channel. Finally, given the desired channel states, the Bayesian equalizer is implemented to reconstruct transmitted symbols. In a series of simulations, binary signals are generated at random with Gaussian noise, and both linear and nonlinear channels are evaluated. The experimental studies demonstrate that the performance (being expressed in terms of accuracy and speed) of the proposed CFCM is superior to the performance of the existing method exploiting the "conventional" Fuzzy C-Means (FCM).

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.609-617
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• 2010

This paper is concerned with the use of a selforganizing map (SOM) to estimate the desired channel states of an unknown digital communication channel for blind equalization. The modification of SOM is accomplished by using the Bayesian likelihood fitness function and the relation between the desired channel states and channel output states. At the end of each clustering epoch, a set of estimated clusters for an unknown channel is chosen as a set of pre-defined desired channel states, and used to extract the channel output states. Next, all of the possible desired channel states are constructed by considering the combinations of extracted channel output states, and a set of the desired states characterized by the maximal value of the Bayesian fitness is subsequently selected for the next SOM clustering epoch. This modification of SOM makes it possible to search the optimal desired channel states of an unknown channel. In simulations, binary signals are generated at random with Gaussian noise, and both linear and nonlinear channels are evaluated. The performance of the proposed method is compared with those of the "conventional" SOM and an existing hybrid genetic algorithm. Relatively high accuracy and fast search speed have been achieved by using the proposed method.

• ETRI Journal
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• v.32 no.1
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• pp.102-111
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• 2010

Recently power attacks on RSA cryptosystems have been widely investigated, and various countermeasures have been proposed. One of the most efficient and secure countermeasures is the message blinding method, which includes the RSA derivative of the binary-with-random-initial-point algorithm on elliptical curve cryptosystems. It is known to be secure against first-order differential power analysis (DPA); however, it is susceptible to second-order DPA. Although second-order DPA gives some solutions for defeating message blinding methods, this kind of attack still has the practical difficulty of how to find the points of interest, that is, the exact moments when intermediate values are being manipulated. In this paper, we propose a practical second-order correlation power analysis (SOCPA). Our attack can easily find points of interest in a power trace and find the private key with a small number of power traces. We also propose an efficient countermeasure which is secure against the proposed SOCPA as well as existing power attacks.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.479-484
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• 2003

We propose a blind watermarking method that embeds a binary pseudo-random sequence (watermarks), (-1, 1), into wavelet dc components, while most watermarking techniques embed watermarks in the middle frequency range for robustness and fidelity. In our scheme, the watermarks are embedded into particular locations to be selected by a key, where some watermark embeddings are skipped to avoid severe degradation in quality. Our robustness is compared to some results registered to the ChechMark [1] that is one of the most popular benchmarking tools.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.971-980
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• 1994

The need increased capacity in the cellular system has resulted in the adoption of digital technology with CDMA as the channel access method. It has been recognized that the distinction of the base station is important for its performance in CDMA, since the same spreading sequences are used by the all base stations. Time offset of the pseudo-random noise binary code are used to distinguish signals received at a mobile station from different base station. But the start of the zero offset PN sequence is chosen arbitrary without the background of the systematic and mathematical elaboration. This paper proposes a mothed that define the start of the zero offset PN sequence mathematically. This paper also discusses a method that can easily calculate the time offset of the received spreading sequence with respect to the zero offset PN sequence.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10B
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• pp.1216-1221
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• 2011

We propose a multiplexed fiber Bragg grating (FBG) sensor network for vessel monitoring to measure the variation of strain and temperature by environmental perturbation based on code division multiple access (CDMA). The center wavelength of FBG was linearly changed by environmental perturbation such as strain and temperature variation so that we could be monitoring the state of sensors. A RSOA was used as optical broadband source and which was modulated by using pseudo random binary sequence (PRBS) signal. The correlation peak of reflected signal from sensor networks was measured. In this paper, we used the sliding correlation techniques for high speed response and dynamic rage of sensors.

• Journal of Power Electronics
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• v.5 no.3
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• pp.198-205
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• 2005

The mechanical system of a drive can often be modeled as a two- or three-mass-system. The load is coupled to the driving motor by a shaft able to perform torsion oscillations. For the automatic tuning of the control, it is necessary to know the mathematical description of the system and the corresponding parameters. As the manpower and setup-time necessary during the commissioning of electrical drives are major cost factors, the development of self-operating identification strategies is a task worth pursuing. This paper presents an identification method which can be utilized for the assisted commissioning of electrical drives. The shaft assembly can be approximated as a two-mass non-rigid mechanical system with four parameters that have to be identified. The mathematical background for an identification procedure is developed and some important implementation issues are addressed. In order to avoid the excitation of the system with its natural resonance frequency, the frequency response can be obtained by exciting the system with a Pseudo Random Binary Signal (PRBS) and using the cross correlation function (CCF) and the auto correlation function (ACF). The reference torque is used as stimulation and the response is the mechanical speed. To determine the parameters, especially in advanced control schemes, a numerical algorithm with excellent convergence characteristics has also been used that can be implemented together with the proposed measurement procedure in order to assist the drive commissioning or to achieve an automatic setting of the control parameters. Simulations and experiments validate the efficiency and reliability of the identification procedure.