Browsing by Author "Shieh, CS"

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A vector neural network for emitter identification
(2002-08-01)
Shieh, CS
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Lin, CT
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電控工程研究所
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Institute of Electrical and Control Engineering
This paper proposes a three-layer vector neural network (VNN) with a supervised learning algorithm suitable for signal classification in general, and for emitter identification (EID) in particular. The VNN can accept interval-value input data as well as scalar input data. The input features of the EID problems include the radio frequency, pulse width, and pulse repetition interval of a received emitter signal. Since the values of these features vary in interval ranges in accordance with a specific radar emitter, the VNN is proposed to process interval-value data in the EID problem. In the training phase, the interval values of the three features are presented to the input nodes of VNN. A new vector-type backpropagation learning algorithm is derived from an error function defined by the VNN's actual output and the desired output indicating the correct emitter type of the corresponding feature intervals. The algorithm can tune the weights of VNN optimally to approximate the nonlinear mapping between a given training set of feature intervals and the corresponding set of desired emitter types. After training, the VNN can be used to identify the sensed scalar-value features from a real-time received emitter signal. A number of simulations are presented to demonstrate the effectiveness and identification capability of VNN, including the two-EID problem and the multi-EID problem with/without additive noise. The simulated results show that the proposed algorithm cannot only accelerate the convergence speed, but it can help avoid getting stuck in bad local minima and achieve higher classification rate.
An embedding algorithm for multiple watermarks
(2003-03-01)
Shieh, CS
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Huang, HC
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Wang, FH
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Pan, JS
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電子工程學系及電子研究所
A new algorithm for embedding several watermarks into the same original source is proposed in this paper. Instead of conventional watermark embedding algorithms that embed one watermark in one specific domain, we propose algorithms for embedding multiple watermarks into different compression domains to protect the ownership of the original images. The proposed schemes for embedding and extraction in different domains vary from the existing methods reported in the literature. Simulation results show their robustness for surviving intentional attacks and, hence, their effectiveness in protecting copyrights. They are also easy to implement.
Direction of arrival estimation based on phase differences using neural fuzzy network
(2000-07-01)
Shieh, CS
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Lin, CT
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電控工程研究所
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Institute of Electrical and Control Engineering
A new high-resolution direction of arrival (DOA) estimation technique using a neural fuzzy network based on phase difference (PD) is proposed in this paper. The conventional DOA estimation method such as MUSIC and MLE, are computationally intensive and difficult to implement in real time. To attach these problems, neural networks have become popular for DOA estimation in recent years. However, the normal neural networks such as multilayer perceptron (MLP) and radial basis function network (RBFN) usually produce the extra problems of low convergence speed and/or large network size (i.e., the number of network parameters is large). Also, the way to decide the network structure is heuristic. To overcome these defects and take use of neural learning ability, a powerful self-constructing neural fuzzy inference network (SONFIN) is used to develop a new DOA estimation algorithm in this paper. By feeding the PD's of received radar-array signals, the trained SONFIN can give high-resolution DOA estimation. The proposed scheme is thus called PD-SONFIN, This new algorithm avoids the need of empirically determining the network size and parameters in normal neural networks due to the powerful on-line structure and parameter learning ability of SONFIN, The PD-SONFIN can always find itself an economical network size in fast learning process. Our simulation results show that the performance of the new algorithm is superior to the RBFN in terms of convergence accuracy, estimation accuracy, sensitivity to noise, and network size.
Genetic watermaking based on transform-domain techniques
(2004-03-01)
Shieh, CS
;
Huang, HC
;
Wang, FH
;
Pan, JS
;
電子工程學系及電子研究所
An innovative watermarking scheme based on genetic algorithms (GA) in the transform domain is proposed. It is robust against watermarking attacks, which are commonly employed in the literature. In addition, the watermarked image quality is also considered. In this paper, we employ GA for optimizing both the fundamentally conflicting requirements. Watermarking with GA is easy for implementation. We also examine the effectiveness of our scheme by checking the fitness function in GA, which includes both factors related to robustness and invisibility. Simulation results also show both the robustness under attacks, and the improvement in watermarked image quality with GA. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Progressive watermarking techniques with genetic algorithms
(2003)
Huang, HC
;
Pan, JS
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Shieh, CS
;
Wang, FH
;
電子工程學系及電子研究所
An innovative watermarking scheme based on progressive transmission with genetic algorithms (GA) is proposed. We implement the watermarking embedding and extraction system in the discrete cosine transform (DCT) domain, and apply the JPEG spectral selection mode for progressive transmission. By employing GA with a proper fitness function into the watermarking system, both the watermark imperceptibility and watermark robustness requirements are considered and optimized. In addition, the embedded watermark can be partly extracted in the receiver side even when the watermarked image is being transmitted. Simulation results show both the robustness and the effectiveness of progressive transmission under different attacking schemes and different bandwidth variations.
The application of tabu search approach to energy allocation and index assignment for VQ-based binary phase shift keying
(2002-01-01)
Shieh, CS
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Huang, HC
;
Pan, JS
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Allocating the energy to the transmitted bits according to their error sensitivities has been shown to significantly overcome the channel errors compared with the codevector index assignment algorithms for vector quantization. In this paper, we combine the tabu energy allocation algorithm with the 'tabu index assignment algorithm' for VQ-based signal compression to reduce the channel distortion caused by the channel decoding error. Experimental results demonstrate that the tabu energy allocation algorithm is superior to the conventional energy allocation algorithm by evaluating the performances under different channel distortion levels. Moreover, the combination of tabu energy allocation and index assignment has better output to compare with tabu index assignment algorithm, conventional energy allocation algorithm and tabu energy allocation algorithm for VQ-based BPSK.