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Mutual Information, the linear prediction model, and CELP Voice Codecs

INFORMATION 2019年第5期10卷 179页

作者： Gibson, Jerry Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

We write the mutual information between an input speech utterance and its reconstruction by a code-excited linear prediction (CELP) codec in terms of the mutual information between the input speech and the contributions due to the short-term predictor, the adaptive codebook, and the fixed codebook. We then show that a recently introduced quantity, the log ratio of entropy powers, can be used to estimate these mutual informations in terms of bits/sample. A key result is that for many common distributions and for Gaussian autoregressive processes, the entropy powers in the ratio can be replaced by the corresponding minimum mean squared errors. We provide examples of estimating CELP codec performance using the new results and compare these to the performance of the adaptive multirate (AMR) codec and other CELP codecs. Similar to rate distortion theory, this method only needs the input source model and the appropriate distortion measure.

关键词： autoregressive models entropy power linear prediction model CELP voice codecs mutual information

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Fall Detection Algorithm Using linear prediction model

Fall Detection Algorithm Using Linear Prediction Model

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Nathasitsophon, Yuphawadee Auephanwiriyakul, Sansanee Theera-Umpon, Nipon Chiang Mai Univ Dept Comp Engn Fac Engn Chiang Mai 50000 Thailand

ISBN: (纸本)9781467351942;9781467351928

One of the health issues in elderly people is the injury from the fall. Some of these injuries might lead to deaths. Thus, a good fall detection algorithm is needed to help reducing a rescuing time for a helper. In this paper, we develop a fall detection algorithm using the linear prediction model with a tri-axis accelerometer. We test the algorithm with the data set that have 11 activities (standing, walking, jumping, falling, running, lying, sitting, getting up (from lying to standing or from sitting to standing), going down (from standing to sitting), accelerating and decelerating) from 17 subjects. The result shows that we can detect all fall activities in both training and blind test data sets with precisions of 90.72% and 93.69%, respectively. The result also shows that we can detect 89.77% and 93.27% of other activities correctly. Although, there are some false alarms, the false alarm rate is small.

关键词： linear prediction model Fall detection Tri-axis accelerometer Healthcare

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An embedded VFAF in DFIG-based wind farms for SSCI mitigation

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2022年 137卷 107765-107765页

作者： Jia, Y. Djurovic, S. Stanojevic, V Ding, L. Vorobev, P. Terzija, V Shandong Univ Sch Elect Engn Jinan 250100 Shandong Peoples R China Univ Manchester Dept Elect & Elect Engn Manchester M13 9PL Lancs England Elektromreza Srbije Belgrade Serbia Skolkovo Inst Sci & Technol Skoltech Ctr Energy Sci & Technol CEST Bolshoy Blvd 30Bld 1 Moscow 121205 Russia

Due to the increasing penetration of wind generations, a new type of sub-synchronous interactions, the so called sub-synchronous control interaction (SSCI), has emerged in power systems in the past decade. Incidents of this type have caused severe consequences in real-life power systems, including equipment damage and loss of power supply. To overcome the impacts and minimize the adverse influences of such phenomenon, this paper proposes a novel varying-frequency adaptive filter (VFAF) in doubly fed induction generators-based wind farms for SSCI mitigation. The proposed VFAF utilizes a linear prediction model and coefficient-based polynomials to analyse the spectral components of the controller signals. In addition, singular value decomposition is used to identify the number of signal components in the controllers. Then, based on the analysis, the VFAF produces compensation signals to modulate the distorted controller signals and thus mitigates the oscillations during SSCI. Based on this mechanism, the VFAF is auto-adaptive to various oscillation frequencies, including those that are time-varying. The above feature is of particularly importance in modern power systems. Testing cases of the VFAF have been conducted in the Power Factory software, and the results verify the effectiveness of the proposed VFAF under relevant system conditions.

关键词： linear prediction model Mitigation Sub-synchronous control interactions Varying-frequency oscillations

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Bandwidth allocation algorithm based on differential BRP models in ethernet PON

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COMPUTER NETWORKS 2020年 177卷 107291-107291页

作者： Wu, Lijuan Gan, Chaoqin Qiao, Hubao Hui, Jianqiang Xu, Zhongsen Shanghai Univ Key Lab Specialty Fiber Opt & Opt Access Networks Shanghai Peoples R China

With the emergence of new services such as high-definition video, cloud computing and virtual reality, the load's bandwidth prediction ability is necessary to support soaring services request bandwidth with diversified characteristics and requirements. In this paper, a novel bandwidth allocation algorithm based on differential bandwidth request prediction (BRP) models is proposed. This algorithm firstly combines linear prediction and nonlinear prediction. According to different characteristics of services, the linear prediction model and the Kalman-filter prediction model are used to predict request bandwidths of corresponding services. By the differential BRP models, the proposed algorithm can greatly better the accuracy of service's request bandwidth prediction and the efficiency of allocating bandwidth. The simulation results demonstrate that the proposed models and algorithm can reduce network's average delay, increase throughput and bandwidth utilization.

关键词： linear prediction model The Kalman-filter prediction model Bandwidth allocation EPON

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Air-borne linear frequency modulation range interrupted continuous-wave SAR for high-resolution imaging

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JOURNAL OF ENGINEERING-JOE 2019年第19期2019卷 5614-5618页

作者： Xu, Wei Huang, Pingping Tan, Weixian Zhang, Zhenhua Dong, Yifan Gao, Zhiqi Inner Mongolia Univ Technol Coll Informat Engn Hohhot 010051 Peoples R China Inner Mongolia Key Lab Radar Technol & Applicat Hohhot 010051 Peoples R China Beijing Res Inst Telemetry Beijing 100076 Peoples R China

To avoid two apertures adopted in air-borne continuous-wave (CW) synthetic aperture radar (SAR) systems, the novel air-borne linear frequency modulation range interrupted continuous wave (LFMRICW) SAR imaging mode is presented here. Different from the conventional air-borne CW imaging mode, it only requires one antenna to transmit radar pulses and receive its echoes. The system design of this mode is given in detail, and its imaging processor based on a linear prediction model (LPM) is proposed according to echo characteristics. Simulation results on distributed targets validate the presented new air-borne imaging scheme and its corresponding imaging processor.

关键词： frequency modulation CW radar radar imaging FM radar synthetic aperture radar air-borne continuous-wave synthetic aperture radar systems continuous wave SAR imaging mode linear prediction model corresponding imaging processor continuous-wave SAR high-resolution imaging air-borne linear frequency modulation range

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Prony's method as a tool for power system identification in Smart Grids

Prony's method as a tool for power system identification in ...

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International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)

作者： Foyen, Sjur Kvammen, Mads-Emil Fosso, Olav Bjarte NTNU Dept Elect Power Eng Trondheim Norway

ISBN: (纸本)9781538649411

This paper investigates the theory, intuition and performance of two known implementations of Prony's method. Such methods are useful for identifying the individual modes of a system without constructing a component-based model. In the Smart Grid, Prony Analysis has been widely used on post-disturbance ring-down measurements, which have been increasingly available with the extensive deployment of PMU's. Both methods decompose the signal into decaying sinusoidals, and estimate the frequency, damping, amplitude and phase of each modal component. The first method is based on the original Prony's method, whilst the second method is based on the thought that the system can be viewed as a digital synthesis problem where the system has the properties of an infinite impulse response filter. Both methods employ EMD-based pre-filtering. Additionally, a cluster based approach is proposed for circumventing the issue of determining model order, so that the true modes of the estimation can be distinguished from the trivial modes.

关键词： Prony Analysis model order modal analysis signal processing linear prediction model linear time-invariant systems clustering empirical mode decomposition

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STATISTICAL ANALYSIS AND modelING OF FORMANT FREQUENCIES OF VOWELS PHONATED BY TRADITIONAL JAPANESE SHIGIN SINGERS

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2017年第5期13卷 1441-1452页

作者： Nakayama, Masashi Kato, Kosuke Matsunaga, Masaru Hiroshima City Univ Grad Sch Informat Sci Asaminami Ku 3-4-1 Ozuka Higashi Hiroshima 7313194 Japan Osaka Univ Off Ind Univ Cocreat 2-8-A201 Yamadaoka Suita Osaka 5650871 Japan Natl Inst Technol Kagawa Coll Dept Elect & Comp Engn 355 Chokushi Takamatsu Kagawa 7618058 Japan

In order to understand the articulation associated with changes in the shape of the vocal fold of traditional Japanese Shigin singers, this study investigated the formant frequencies of anechoic recordings of the quasi-steady-state portions of vowels phonated by six trained Shigin singers. Results show that each of the four formant frequencies (F-1, F-2, F-3, and F-4) of the vowels(/u/, /o/, /a/, /e/,and / i/) phonated by Shigin singers differed from those of other singing styles and those of the normal speech mode. The F-1, F-2, and F-3 of the vowels phonated by Shigin singers were statistically modeled as a function of the singer's gender, phonated vowels, loudness level, and phonation frequency. Each of the models was described using a simple linear equation. These findings are expected to be useful for synthesis of the singing voice, development of training support systems, and understanding of the voice production mechanisms of singers.

关键词： Shigin singing Speech Formant frequency Statistical modeling linear prediction model

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Blind detection of median filtering using linear and nonlinear descriptors

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MULTIMEDIA TOOLS AND APPLICATIONS 2016年第4期75卷 2327-2346页

作者： Shen, Zhaoyi Ni, Jiangqun Chen, Chenglong Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China

Recently, for the recovery of images' processing history, passive forensics of possible manipulations has attracted wide interest. In particular, due to highly non-linearity, median filtering (MF) usually serves as an effective tool of counter forensic techniques for other image operations. Therefore, the importance of median filtering detection is self-evident. In this paper, through analysing the pixel differences of images, we found the indications to study the complex correlations introduced by median filtering and adopt two sets of describing features to measure them. More Specifically, we utilize a linear prediction model for the differences of image that is computed along a specific direction and estimate the prediction coefficients to construct a linear descriptor L. Besides, we make use of the histogram of rotation invariant local binary pattern (LBP) to form a nonlinear descriptor N. According to our observation, we also propose an enhanced feature EF to further improve the detection performance. Based on these, we present a novel median filtering detection scheme incorporating both the linear and nonlinear descriptors. Extensive experiments are carried out, which demonstrate that our proposed scheme gains favorable performance comparing to state-of-the-art methods, especially for low resolution images and JPEG compressed images, and shows resistance to noise attack.

关键词： Median filtering Digital image forensics linear prediction model LBP

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prediction of Temperature and Relative Humidity in Greenhouse Based on the Combination of DGM(1,1) and linear model

Prediction of Temperature and Relative Humidity in Greenhous...

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IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)

作者： Yin Jingjing Anhui Vocat Coll Def Technol Dept Mech & Elect Engn Luan Peoples R China

ISBN: (纸本)9781479969890

Some high-grade flowers in greenhouse have very high demand on temperature and relative humidity. As the greenhouse is a system with great inertia, appropriate control methods must be adopted ahead in order to guarantee the temperature and relative humidity in reasonable scopes. The accurate prediction of temperature and relative humidity is the important prerequisite for adopting appropriate control methods. A combined prediction model was proposed based on the discrete grey model DGM(1,1) and linear model. In order to verify the validity of the DGM(1,1) model, the temperature and relative humidity were actually measured in a greenhouse. The results show that the largest relative error predicted by the combined model is 2.94% for temperature and 6.11% for relative humidity, which is superior to those of DGM(1,1) model and linear model only used respectively. At last, the factors affecting the prediction accuracy were analyzed. The change of control devices' working mode and the length of sampling period are two main influence factors.

关键词： DGM(1,1) model linear prediction model Greenhouse Temperature Relative humidity

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Effective Load Scheduling of Residential Consumers based on Dynamic Pricing with Price prediction Capabilities 1

Effective Load Scheduling of Residential Consumers based on ...

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1st IEEE International Conference on Power Electronics, Intelligent Control, and Energy Systems (ICPEICES)

作者： Pal, Shalini Kumar, Rajesh Malviya Natl Inst Technol Jaipur Rajasthan India

ISBN: (纸本)9781467385879

Demand response (DR) sustains an influential role in today's smart grid. DR program is an initiative to enhance the performance of electricity price market and the stability of the power system. Price based DR programs have a significant part in the residential customer activities. In the present scenario, the flat tariffs are replaced by real-time pricing (RTP) models due to their economic benefits and the environment supportive behave. The RTP models are capable of providing a chance to customers to reduce their electricity bills. The customers can communicate their demand information to the utility and get back the prices via smart metering technologies. In this paper, an automatic load control approach with dynamic pricing models is implemented for residential consumers. In real time pricing environment, it is necessary to have price prediction capabilities. Here, the linear prediction model (LPM) and artificial neural network are implemented for predicting the prices. For optimization purpose mixed binary linear programming (MBLP) computations are used. To validate the performance of system simulation results has shown the better performance with the different scenario.

关键词： Demand Response Real Time Pricing Automatic Load Control linear prediction model Artificial Neural Network Mixed Primary linear Programming

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