• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.3
• /
• pp.290-297
• /
• 2004

The control laws for cart-pole system are studied to see the schemes on which the control laws are made. Also, the odd symmetry of the relation between the output of the control laws and the system state vector is observed. Utilizing the symmetry in quantizing the system state variables and implementing the control laws into look-up table is discussed. Then, a CMAC is trained for a nonlinear control law for a cart-pole system such that the symmetry is conserved and its learning performance is evaluated. It is found that utilizing the symmetry is to reduce the memory requirement as well as the training period while improving the learning quality in terms of preserving the symmetry.

• Journal of Intelligence and Information Systems
• /
• v.15 no.2
• /
• pp.49-59
• /
• 2009

Contents-based image retrieval methods are in general more objective and effective than text-based image retrieval algorithms since they use color and texture in search and avoid annotating all images for search. SIM(Self-organizing Image browsing Map) is one of contents-based image retrieval algorithms that uses only browsable mapping results obtained by SOM(Self Organizing Map). However, SOM may have an error in selecting the right BMU in learning phase if there are similar nodes with distorted color information due to the intensity of light or objects' movements in the image. Such images may be mapped into other grouping nodes thus the search rate could be decreased by this effect. In this paper, we propose an improved SIM that uses HSV color model in extracting image features with color quantization. In order to avoid unexpected learning error mentioned above, our SOM consists of two layers. In learning phase, SOM layer 1 has the color feature vectors as input. After learning SOM Layer 1, the connection weights of this layer become the input of SOM Layer 2 and re-learning occurs. With this multi-layered SOM learning, we can avoid mapping errors among similar nodes of different color information. In search, we put the query image vector into SOM layer 2 and select nodes of SOM layer 1 that connects with chosen BMU of SOM layer 2. In experiment, we verified that the proposed SIM was better than the original SIM and avoid mapping error effectively.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.4
• /
• pp.714-725
• /
• 1997

This paper proposes an image compression method using the wavelet transform and bit-plane coding of wavelet coefficients. The hierarchical application of wavelet transform to an image produces one low resoluation(the subband with lowest frequency) image and several high frequency subbands. In the proposed method, the low resolution image is compressed by a lossless method at 8 bits per each coefficient. However, the high frequency subbands are decomposed into 8 bit planes. With an adptive block coding method, the decomposed bit planes are effectively compressed using localized edge information in each bit plane. In addition, the propsoed method can control bit rates by selectively eliminating lessimportant subbands of low significant bit planes. Experimental results show that the proposed scheme has better performance in the peak signal to noise ratio (PSNR) and compression rate than conventional image coding methods using the wavelet transform and vector quantization.

• Journal of Broadcast Engineering
• /
• v.12 no.6
• /
• pp.596-610
• /
• 2007

In order to reduce the complexity of SVC encoding, we introduce a fast mode decision method in the enhancement layers of spatial scalability by selectively performing the inter-layer residual prediction of SVC. The Inter-layer residual prediction coding in Scalable Video Coding has a large advantage of enhancing the coding efficiency since it utilizes the correlation between two residuals from a lower spatial layer and its next higher spatial layer. However, this entails the dramatical increase in the complexity of SVC encoders. The proposed method is to analyze the characteristics of integer transform coefficients for the subtracted signal for two residuals from lower and upper spatial layers. Then it selectively performs the inter-layer residual prediction coding and rate-distortion optimizations in the upper spatial enhancement layer if the SAD values of residuals exceed adaptive threshold values. Therefore, by classifying the residuals according to the properties of integer-transform coefficients only with SAD of residuals between two layers, the SVC encoder can perform the inter-layer residual coding selectively, thus significantly reducing the total required encoding time. The proposed method results in reduction of the total encoding time with 51.5% in average while maintaining the RD performance with negligible amounts of quality degradation.

• The Journal of the Acoustical Society of Korea
• /
• v.24 no.7
• /
• pp.410-415
• /
• 2005

Recently, most of the speaker verification systems are based on the pattern recognition approach method. And performance of the pattern-classifier depends on how to classify a variety of speakers' feature parameters. In order to classify feature parameters efficiently and effectively, it is of great importance to enlarge variations between speakers and effectively measure distances between feature parameters. Therefore, this paper would suggest the positively mixed model scheme that can enlarge inter-speaker variation by searching the individual model with world model at the same time. During decision procedure, we can maximize inter-speaker variation by using the proposed mixed model scheme. We also make use of a symbol probability weighting function in this system so as to reduce vector quantization errors by measuring symbol probability derived from the distance rate of between the world codebook and individual codebook. As the result of our experiment using this method, we could halve the Detection Cost Function (DCF) of the system from $2.37\%\;to\;1.16\%$.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.6 s.38
• /
• pp.47-54
• /
• 2005

In the most of speaker recognition system, speaker's characteristics is extracted from acoustic parameter by speech analysis and we make speaker's reference pattern. Parameters used in speaker recognition system are desirable expressing speaker's characteristics fully and being a few difference whenever it is spoken. Therefore we su99est following to solve this problem. This paper is proposed to use strong spectrum characteristic in non-noise circumstance and prosodic information in noise circumstance. In a stage of making code book, we make the number of data we need to combine spectrum characteristic and Prosodic information. We decide acceptance or rejection comparing test pattern and each model distance. As a result, we obtained more improved recognition rate than we use spectrum and prosodic information especially we obtained stational recognition rate in noise circumstance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.26 no.3
• /
• pp.292-299
• /
• 2015

An envelope elimination and restoration transmitter that uses a tri-level envelope encoding scheme is presented for improving the efficiency and linearity of the system. The proposed structure amplifies the same magnitude signal regardless of the input peak-to-average power ratio and reduces the quantization noise by spreading out the noise to the out-of-band frequency, resulting in the enhancement of power efficiency. An improved linearity is also obtained by providing a new timing mismatch calibration technique between the envelope and phase signal. Implementation in a 130 nm CMOS process, transmitter measurements on a 20-MHz long-term evolution input signal show an error vector magnitude of 3.7 % and an adjacent channel leakage ratio of 37.5 dBc at 2.13 GHz carrier frequency.

• Journal of Broadcast Engineering
• /
• v.14 no.4
• /
• pp.387-396
• /
• 2009

No-Reference video-quality assessments are divided into two kinds of metrics based on decoding pixel domain or the bitstream one. Traditional full-/reduced- reference methods have difficulty to be deployed as realtime video transmission because it has problems of additional data, complexity, and assessment accuracy. This paper presents simple and highly accurate no-reference video-quality assessment in realtime video transmission. Our proposed method uses quantization parameter, motion vector, and information of transmission error. To evaluate performance of the proposed algorithm, we perform subjective test of video quality with the ITU-T P.910 Absolute Category Rating(ACR) method and compare our proposed algorithm with the subjective quality assessment method. Experimental results show the proposed quality metric has a high correlation (85%) in terms of subjective quality assessment.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.7
• /
• pp.63-68
• /
• 2001

This paper describes the details of ITU-T SGIS G.729A speech coder implementation using ARM9 Thumb/sup R/ processor core and various techniques used in the optimization process. ITU-T G.729 speech coder is the standard of the toll quality 8 kbit/s speech coding. The input to the speech encoder is assumed to be a 16 bits PCM signal at a sampling rate of 8000 samples per second. G.729A is reduced complexity version of the G.729 coder. This version is bit stream interoperable with the full version. The implemented coder requires 34.8 MIPS for the encoder and 8.1 MIPS for the decoder, 36.5 kBytes of program ROM and 6.3 kBytes of data RAM, respectively. The implemented coder is tested against the set of 9 test vectors provided by ITU-T for bit exact implementation.

• The Journal of the Acoustical Society of Korea
• /
• v.10 no.4
• /
• pp.38-47
• /
• 1991

The frequency variation among speakers is one of problems in the speech recognition. This paper applies fuzzy theory to solve the variation problem of frequency features. Reference patterns are expressed by fuzzified patterns which are produced by the peak frequency and the peak energy extracted from codebooks which are generated from training words uttered by several speakers, as they should include common features of speech signals. Words are recognized by fuzzy inference which uses the certainty factor between the reference patterns and the test fuzzified patterns which are produced by the peak frequency and the peak energy extracted from the power spectrum of input speech signals. Practically, in computing the certainty factor, to reduce memory capacity and computation requirements we propose a new equation which calculates the improved certainty factor using only the difference between two fuzzy values. As a result of experiments to test this word recognition method by fuzzy interence with Korean digits, it is shown that this word recognition method using the new equation presented in this paper, can solve the variation problem of frequency features and that the memory capacity and computation requirements are reduced.