• Title/Summary/Keyword: Vector Reduce

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Coding History Detection of Speech Signal using Deep Neural Network (심층 신경망을 이용한 음성 신호의 부호화 이력 검출)

  • Cho, Hyo-Jin;Jang, Won;Shin, Seong-Hyeon;Park, Hochong
    • Journal of Broadcast Engineering
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    • v.23 no.1
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    • pp.86-92
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    • 2018
  • In this paper, we propose a method for coding history detection of digital speech signal. In digital speech communication and storage, the signal is encoded to reduce the number of bits. Therefore, when a speech signal waveform is given, we need to detect its coding history so that we can determine whether the signal is an original or an coded one, and if coded, determine the number of times of coding. In this paper, we propose a coding history detection method for 12.2kbps AMR codec in terms of original, single coding, and double coding. The proposed method extracts a speech-specific feature vector from the given speech, and models the feature vector using a deep neural network. We confirm that the proposed feature vector provides better performance in coding history detection than the feature vector computed from the general spectrogram.

Segmented Douglas-Peucker Algorithm Based on the Node Importance

  • Wang, Xiaofei;Yang, Wei;Liu, Yan;Sun, Rui;Hu, Jun;Yang, Longcheng;Hou, Boyang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.4
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    • pp.1562-1578
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    • 2020
  • Vector data compression algorithm can meet requirements of different levels and scales by reducing the data amount of vector graphics, so as to reduce the transmission, processing time and storage overhead of data. In view of the fact that large threshold leading to comparatively large error in Douglas-Peucker vector data compression algorithm, which has difficulty in maintaining the uncertainty of shape features and threshold selection, a segmented Douglas-Peucker algorithm based on node importance is proposed. Firstly, the algorithm uses the vertical chord ratio as the main feature to detect and extract the critical points with large contribution to the shape of the curve, so as to ensure its basic shape. Then, combined with the radial distance constraint, it selects the maximum point as the critical point, and introduces the threshold related to the scale to merge and adjust the critical points, so as to realize local feature extraction between two critical points to meet the requirements in accuracy. Finally, through a large number of different vector data sets, the improved algorithm is analyzed and evaluated from qualitative and quantitative aspects. Experimental results indicate that the improved vector data compression algorithm is better than Douglas-Peucker algorithm in shape retention, compression error, results simplification and time efficiency.

Robust MVDR Adaptive Array by Efficient Subspace Tracking (효율적인 부공간 추적에 의한 강인한 MVDR 적응 어레이)

  • Choi, Yang-Ho
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.9
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    • pp.148-156
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    • 2014
  • In the MVDR (minimum variance distortionless response) adaptive array, its performance could be greatly deteriorated in the presence of steering vector errors as the desired signal is treated as an interference. This paper suggests an computationally simple adaptive beamforming method which is robust against these errors. In the proposed method, a minimization problem that is formulated according to the DCB (doubly constrained beamforming) principle is solved to find a solution vector, which is in turn projected onto a subspace to obtain a new steering vector. The minimization problem and the subspace projection are dealt with using some principal eigenpairs, which are obtained using a modified PASTd(projection approximation subspace tracking with deflation). We improve the existing MPASTd(modified PASTd) algorithm such that the computational complexity is reduced. The proposed beamforming method can significantly reduce the complexity as compared with the conventional ones directly eigendecomposing an estimate of the corelation matrix to find all eigenvalues and eigenvectors. Moreover, the proposed method is shown, through simulation, to provide performance improvement over the conventional ones.

Sample-Adaptive Product Quantization and Design Algorithm (표본 적응 프러덕트 양자화와 설계 알고리즘)

  • 김동식;박섭형
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.12B
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    • pp.2391-2400
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    • 1999
  • Vector quantizer (VQ) is an efficient data compression technique for low bit rate applications. However, the major disadvantage of VQ is its encoding complexity which increases dramatically as the vector dimension and bit rate increase. Even though one can use a modified VQ to reduce the encoding complexity, it is nearly impossible to implement such a VQ at a high bit rate or for a large vector dimension because of the enormously large memory requirement for the codebook and the very large training sequence (TS) size. To overcome this difficulty, in this paper we propose a novel structurally constrained VQ for the high bit rate and the large vector dimension cases in order to obtain VQ-level performance. Furthermore, this VQ can be extended to the low bit rate applications. The proposed quantization scheme has a form of feed-forward adaptive quantizer with a short adaptation period. Hence, we call this quantization scheme sample-adaptive product quantizer (SAPQ). SAPQ can provide a 2 ~3dB improvement over the Lloyd-Max scalar quantizers.

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Design of a 7-bit 2GSPS Folding/Interpolation A/D Converter with a Self-Calibrated Vector Generator (자체보정 벡터 발생기를 이용한 7-bit 2GSPS A/D Converter의 설계)

  • Kim, Seung-Hun;Kim, Dae-Yun;Song, Min-Kyu
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.48 no.4
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    • pp.14-23
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    • 2011
  • In this paper, a 7-bit 2GSPS folding/interpolation A/D Converter(ADC) with a Self-Calibrated Vector Generator is proposed. The ADC structure is based on a folding/interpolation architecture whose folding/interpolation rate is 4 and 8, respectively. A cascaded preprocessing block is not only used in order to drive the high input signal frequency, but the resistive interpolation is also used to reduce the power consumption. Based on a novel self-calibrated vector generator, further, offset errors due to device mismatch, parasitic resistors. and parasitic capacitance can be reduced. The chip has been fabricated with a 1.2V 0.13um 1-poly 7-metal CMOS technology. The effective chip area including the calibration circuit is 2.5$mm^2$. SNDR is about 39.49dB when the input frequency is 9MHz at 2GHz sampling frequency. The SNDR is improved by 3dB with the calibration circuit.

Real-Time Implementation of the EHSX Speech Coder Using a Floating Point DSP (부동 소수점 DSP를 이용한 4kbps EHSX 음성 부호화기의 실시간 구현)

  • 이인성;박동원;김정호
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.5
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    • pp.420-427
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    • 2004
  • This paper presents real time implementation of 4kbps EHSX (Enhanced Harmonic Stochastic Excitation) speech coder that combines the harmonic vector excitation coding with time-separated transition coding. The harmonic vector excitation coding uses the harmonic excitation coding for voiced frames and used the vector excitation coding with the structure of analysis-by-synthesis for unvoiced frames, respectively. For transition frames mixed with voiced and unvoiced signal, we use the time-separated transition coding. In this paper. we present the optimization methods of implementation speech coder on the EMS320C6701/sup (R)/ DSP. To reduce the complex for real-time implementation. we perform the optimization method in algorithm by replacing the complex sinusoidal synthesis method with IFFT. and we apply fully pipelines hand assembly coding after converting it from floating source to fixed source. To generate a more efficient code. we also make use or the available EMS320C6701/sup (R)/ resources such as Fastest67x library and memory organization.

The Performance Improvement of MCMA Adaptive Equalization in 16-QAM Signal using Dual Weight Vector (이중 가중치 벡터를 이용한 16-QAM 신호의 MCMA 적응 등화 성능 개선)

  • Yoon, Jae-Sun;Lim, Seung-Gag
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.6
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    • pp.41-47
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    • 2011
  • This paper is concerned with the DW-MCMA(Dual Weight vector Modified Constant Modulus Algorithm) adaptive equalization algorithm using the dual weight vector in order to improve the convergence characteristic and residual inter-symbol interference which are used as the performance index for an adaptive equalizer. The equalizer is used to reduce the distortion caused by the inter-symbol interference on the wireless and the wired band-limited channel that connect the transmitting system and receiving system. The CMA is widely known as the representative algorithm for equalization. In order to transmitting the mass information with a high speed through the channels, a fast convergence speed in the equalizer performance that is able to minimize overhead needed for equalization is acquired. In this paper, By the computer simulation, we confirmed that the proposed DW-MCMA has the faster convergence speed and the smaller residual inter-symbol interference than the conventional CMA and MCMA.

Rotor Flux Estimation of an Induction Motor using the Extended Luenberger Observer (확장된 루엔버거 관측기를 이용한 유도전동기 회전자 자속 추정)

  • 조금배;최연옥;정삼용
    • The Transactions of the Korean Institute of Power Electronics
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    • v.6 no.2
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    • pp.115-124
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    • 2001
  • In this paper, authors propose a new nonlinear rotor flux observer for rotor field oriented control of an induction motor which is designed based on the extended Luenberger Observer theory. Extended Luenberger Observer requires minimal solution of nonlinear partial differential equation on its coordinate transformation and linearization needed on a nonlinear observer design in general. The proposed rotor flux observer is derived from the 2 phase model of induction motor on the orthogonal coordination and it has the reduce gain matrix. Simulation and experimentation were performed under the conventional indirect vector control and direct vector control with the proposed observer at different rotor resistance. Simulation results show that the convergence of the proposed observer is influenced by the chosen eigenvalues. Experimentation results on load operation show the direct vector control with the proposed observer is better than the indirect vector control to maintain the characteristics of the vector control.

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A Motion Vector Re-Estimation Algorithm for Image Downscaling in Discrete Cosine Transform Domain (이산여현변환 공간에서의 영상 축소를 위한 움직임 벡터 재추정)

  • Kim, Woong-Hee;Oh, Seung-Kyun;Park, Hyun-Wook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.5
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    • pp.494-503
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    • 2002
  • A motion vector re-estimation algorithm for image downscaling in discrete consine transform domain is presented. Kernel functions are difined using SAD (Aum of Absolute Difference) and edge information of a macroblock. The proposed method uses these kernel functions to re-estimate a new motion vector of the downscaled image. The motion vectors from the incoming bitstream of transcoder are reused to reduce computation burden of the block-matching motion estimation, and we also reuse the given motion vectors. Several experiments in this paper show that the computation efficiency and the PSNR (Peak Signal to Noise Ratio) and better than the previous methods.

The Edge-Based Motion Vector Processing Based on Variable Weighted Vector Median Filter (에지 기반 가변 가중치 벡터 중앙값 필터를 이용한 움직임 벡터 처리)

  • Park, Ju-Hyun;Kim, Young-Chul;Hong, Sung-Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.11C
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    • pp.940-947
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    • 2010
  • Motion Compensated Frame Interpolation(MCFI) has been used to reduce motion jerkiness for dynamic scenes and motion blurriness for LCD-panel display as post processing for high quality display. However, MCFI that directly uses the motion information often suffers from annoying artifacts such as blockiness, ghost effects, and deformed structures. So in this paper, we propose a novel edge-based adaptively weighted vector median filter as post-processing. At first, the proposed method generates an edge direction map through a sobel mask and a weighted maximum frequent filter. And then, outlier MVs are removed by average of angle difference and replaced by a median MV of $3{\times}3$ window. Finally, weighted vector median filter adjusts the weighting values based on edge direction derived from spatial coherence between the edge direction continuity and motion vector. The results show that the performance of PSNR and SSIM are higher up to 0.5 ~ 1 dB and 0.4 ~ 0.8 %, respectively.