• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.359-364
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• 2004

In this paper, we implemented real-time speaker undependent speech recognizer that is robust in noise environment using DSP(Digital Signal Processor). Implemented system is composed of TMS320C32 that is floating-point DSP of Texas Instrument Inc. and CODEC for real-time speech input. Speech feature parameter of the speech recognizer used robust feature parameter in noise environment that is transformed feature space of MFCC(met frequency cepstral coefficient) using ICA(Independent Component Analysis) on behalf of MFCC. In recognition result in noise environment, we hew that recognition performance of ICA feature parameter is superior than that of MFCC.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.11
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• pp.31-38
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• 1998

This paper deals with CBS(Cycle Base Simulator) design of a 32 bit floating point DSP(Digital Signal Processor). The CBS has been developed for TMS320C30 compatible DSP and will be used to confirm the architecture, functions of sub-blocks, and control signals of the chip before the detailed logic design starts with VHDL. The outputs from CBS are used as important references at gate level design step because they give us control signals, output values of important blocks, values from internal buses and registers at each pipeline step, which are not available from the commercial simulator of DSP. In addition to core functions, it has various interfaces for efficient execution and convenient result display, CBS is verified through comparison with results from the commercial simulator for many application algorithms and its simulation speed is as fast as several tenth of that of logic simulation with VHDL. CBS in this work is for a specific DSP, but the concept may be applicable to other VLSI design.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9A
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• pp.931-939
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• 2007

This paper describes the system which automatically generates instruction-set simulators cores using the SMDL. SMDL describes structure and instruction-set information of a target DSP machine. Analyzing behavioral information of each pipeline stage of all instructions on a target ASIPS, the proposed system automatically generates a cycle-accurate instruction set simulator in C++ for a target processor. The proposed system has been tested by generating instruction-set simulators for ARM9E-S, ADSP-TS20x, and TMS320C2x architectures. Experiments were performed by checking the functions of the $4{\times}4$ matrix multiplication, 16-bit IIR filter, 32-bit multiplication, and the FFT using the generated simulators. Experimental results show the functional accuracy of the generated simulators.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.7
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• pp.103-108
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• 2007

Neural network is used in many fields of control systems currently. However, It is not easy to obtain input-output pattern when neural network is used for the system of a single feedback controller and it is difficult to get satisfied performance with neural network when load changes rapidly or disturbance is applied. To resolve these problems, this paper proposes a new mode to implement a neural network controller by installing a real object in place of activation function of Neural Network output node. As the Neural Network self adaptive control system is designed in simple structure neural network input-output pattern problem is solved naturally and real tin Loaming becomes possible through general back propagation algorithm. The effect of the proposed Neural Network self adaptive control algorithm was verified in a test of controlling the speed of a A.C. servo motor equipped with a high speed computing capable DSP (TMS320C32) on which the proposed algorithm was loaded.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.162-169
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• 1999

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital Signal Processors. Digital signal processors DSPs. are micro-processors that are particularly developed for variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a biable computatinal tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for implementation of real-time control of robot system by the simulation and experiment.

• Journal of Astronomy and Space Sciences
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• v.13 no.2
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• pp.163-172
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• 1996

The objective of this paper is to show how digital signal processing experiment(DSPE) was designed and to present its experimental results in orbit and on the ground. The multi-missional and flexible DSPE was designed in a reliable manner. Among several experiments executed in orbit and on the ground, a high-speed(19.2kbps) software modulator experiment was discussed in this paper. A 32bit floating-type TMS320C30, which was developed for commercial purposes, was used on LEO micro-satellites, KITSAT-1 and KITSAT-2. This digital signal processor(DSP) can be applied to the various payloads of the next generation satellites.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.74-86
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• 2005

In this paper, we proposed an algorithm for the approximation of high order FIR filters by low order IIR filters to efficient implementing two channel 3-D surround sound systems using Head-related transfer functions(HRTFs). The algorithm is based on a concept of the balanced model reduction. The binaural sounds using the approximated HRTFs are reproduced by headphone, and serves as a cue of sound image localization. HRTFs of dummy-head are approximated from 512-order FIR filters by 32-order IIR filters and compare with each other. .Experiment of sound image are carried out for 10 participants. We perform the experiment based on computer simulation and hardware experiment with TMS320C32. The results of the experiments show that the localization using the approximated HRTFs is the same accuracy as the case of FIR filters that simulate the HRTFs.

• The Journal of the Acoustical Society of Korea
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• v.32 no.4
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• pp.346-353
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• 2013

This paper deals with the implementation of a high-quality audio system for karaoke. For improving the key/tempo changes performance, we separated the audio into many musical instrument channels. By separating musical instrument channels, high-quality key/tempo changes can be achieved and we confirmed this using the cross-correlation distribution and the MOS evaluation. The improved audio system was implemented using the TMS320C6747 DSP with fixed/floating-point operations. The implemented audio system can perform the multi-channel WMA decoding, the MP3 encoding/decoding, the wav playing, the EQ, and the key/tempo changes in real time. The WMA channels used for processing the separated instrument channels. The audio system includs the MP3 encoding/decoding function for playing and recording and the wav channel for the effect sound.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.935-938
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• 2000

본 논문에서는 음성 인식을 이용하여 전화를 교환해주는 자동 교환 시스템을 구현하고, 성능을 평가하였다. 구현된 시스템에는 필수적인 음성인식 이외에도 DSP 진단 기능, 인식 대상 어휘의 추가 및 변경기능, 음성 수집 기능 등이 구현 되었다. SCHMM (Semi-Continuous Hidden Markov Model)을 이용한 전화망에서의 화자 독립 고립 단어 가변 어휘 인식을 대상으로 하였으며, 실시간 구현을 위하여 Texas Instrument 사의 TMS320C32를 사용하였다〔6〕. 인식 어휘는 부서명 및 인명이고 1300여 단어일 때, 인식 성능은 91.5%이다.