Готові списки джерел за темами / Predictive quantization

Добірка наукової літератури з теми "Predictive quantization"

Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями

Оберіть тип джерела:

Зміст

Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Predictive quantization".

Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.

Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.

Статті в журналах з теми "Predictive quantization"

1

Ngan, K. N., and H. C. Koh. "Predictive classified vector quantization." IEEE Transactions on Image Processing 1, no. 3 (July 1992): 269–80. http://dx.doi.org/10.1109/83.148602.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Dubnov, Shlomo. "Predictive Quantization and Symbolic Dynamics." Algorithms 15, no. 12 (December 19, 2022): 484. http://dx.doi.org/10.3390/a15120484.

Повний текст джерела
Анотація:
Capturing long-term statistics of signals and time series is important for modeling recurrent phenomena, especially when such recurrences are a-periodic and can be characterized by the approximate repetition of variable length motifs, such as patterns in human gestures and trends in financial time series or musical melodies. Regressive and auto-regressive models that are common in such problems, both analytically derived and neural network-based, often suffer from limited memory or tend to accumulate errors, making them sensitive during training. Moreover, such models often assume stationary signal statistics, which makes it difficult to deal with switching regimes or conditional signal dynamics. In this paper, we describe a method for time series modeling that is based on adaptive symbolization that maximizes the predictive information of the resulting sequence. Using approximate string-matching methods, the initial vectorized sequence is quantized into a discrete representation with a variable quantization threshold. Finding an optimal signal embedding is formulated in terms of a predictive bottleneck problem that takes into account the trade-off between representation and prediction accuracy. Several downstream applications based on discrete representation are described in this paper, which includes an analysis of the symbolic dynamics of recurrence statistics, motif extraction, segmentation, query matching, and the estimation of transfer entropy between parallel signals.
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Klautau, A. B. R. "Predictive vector quantization with intrablock prediction support region." IEEE Transactions on Image Processing 8, no. 2 (1999): 293–95. http://dx.doi.org/10.1109/83.743862.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Hsueh-Ming Hang and J. Woods. "Predictive Vector Quantization of Images." IEEE Transactions on Communications 33, no. 11 (November 1985): 1208–19. http://dx.doi.org/10.1109/tcom.1985.1096238.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Linden, J. "Channel optimized predictive vector quantization." IEEE Transactions on Speech and Audio Processing 8, no. 4 (July 2000): 370–84. http://dx.doi.org/10.1109/89.848219.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Rizvi, Syed A. "Entropy‐constrained predictive residual vector quantization." Optical Engineering 35, no. 1 (January 1, 1996): 187. http://dx.doi.org/10.1117/1.600889.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Marcellin, M. W., T. R. Fischer, and J. D. Gibson. "Predictive trellis coded quantization of speech." IEEE Transactions on Acoustics, Speech, and Signal Processing 38, no. 1 (1990): 46–55. http://dx.doi.org/10.1109/29.45617.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Schwarz, Stefan, and Markus Rupp. "Predictive Quantization on the Stiefel Manifold." IEEE Signal Processing Letters 22, no. 2 (February 2015): 234–38. http://dx.doi.org/10.1109/lsp.2014.2354258.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Wu, Yung-Gi. "Predictive classifier for image vector quantization." Optical Engineering 39, no. 9 (September 1, 2000): 2372. http://dx.doi.org/10.1117/1.1286465.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Rizvi, S. A., and N. M. Nasrabadi. "Predictive residual vector quantization [image coding]." IEEE Transactions on Image Processing 4, no. 11 (1995): 1482–95. http://dx.doi.org/10.1109/83.469930.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Дисертації з теми "Predictive quantization"

1

Soong, Michael. "Predictive split vector quantization for speech coding." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=68054.

Повний текст джерела
Анотація:
The purpose of this thesis is to examine techniques for efficiently coding speech Linear Predictive Coding (LPC) coefficients. Vector Quantization (VQ) is an efficient approach to encode speech at low bit rates. However its exponentially growing complexity poses a formidable barrier. Thus a structured vector quantizer is normally used instead.
Summation Product Codes (SPCs) are a family of structured vector quantizers that circumvent the complexity obstacle. The performance of SPC vector quantizers can be traded off against their storage and encoding complexity. Besides the complexity factors, the design algorithm can also affect the performance of the quantizer. The conventional generalized Lloyd's algorithm (GLA) generates sub-optimal codebooks. For particular SPC such as multistage VQ, the GLA is applied to design the stage codebooks stage-by-stage. Joint design algorithms on the other hand update all the stage codebooks simultaneously.
In this thesis, a general formulation and an algorithm solution to the joint codebook design problem is provided for the SPCs. The key to this algorithm is that every PC has a reference product codebook which minimizes the overall distortion. This joint design algorithm is tested with a novel SPC, namely "Predictive Split VQ (PSVQ)".
VQ of speech Line Spectral Frequencies (LSF's) using PSVQ is also presented. A result in this work is that PSVQ, designed using the joint codebook design algorithm requires only 20 bits/frame(20 ms) for transparent coding of a 10$ sp{ rm th}$ order LSF's parameters.
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Abousleman, Glen Patrick. "Entropy-constrained predictive trellis coded quantization and compression of hyperspectral imagery." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/186748.

Повний текст джерела
Анотація:
A training-sequence-based entropy-constrained predictive trellis coded quantization (ECPTCQ) scheme is presented for encoding autoregressive sources. For encoding a first-order Gauss-Markov source, the MSE performance of an 8-state ECPTCQ system exceeds that of entropy-constrained DPCM by up to 1.0 dB. In addition, three systems--an ECPTCQ system, a 3-D Discrete Cosine Transform (DCT) system and a hybrid system--are presented for compression of hyperspectral imagery which utilize trellis coded quantization (TCQ). Specifically, the first system utilizes a 2-D DCT and ECPTCQ. The 2-D DCT is used to transform all nonoverlapping 8 x 8 blocks of each band. Thereafter, ECPTCQ is used to encode the transform coefficients in the spectral dimension. The 3-D DCT system uses TCQ to encode transform coefficients resulting from the application of an 8 x 8 x 8 DCT. The hybrid system uses DPCM to spectrally decorrelate the data, while a 2-D DCT coding scheme is used for spatial decorrelation. Side information and rate allocation strategies for all systems are discussed. Entropy-constrained codebooks are optimized for various generalized Gaussian distributions using a modified version of the generalized Lloyd algorithm. The first system can compress a hyperspectral image sequence at 0.125 bits/pixel/band while retaining an average peak signal-to-noise ratio of greater than 43 dB over the spectral bands. The 3-D DCT and hybrid systems achieve compression ratios of 77:1 and 69:1 while maintaining average peak signal-to-noise ratios of 40.75 dB and 40.29 dB, respectively, over the coded bands.
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Wang, Yan. "Predictive boundary point adaptation and vector quantization compression algorithms for CMOS image sensors /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?ECED%202007%20WANGY.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Rivera, Hernández Sergio. "Tensorial spacetime geometries carrying predictive, interpretable and quantizable matter dynamics." Phd thesis, Universität Potsdam, 2012. http://opus.kobv.de/ubp/volltexte/2012/6186/.

Повний текст джерела
Анотація:
Which tensor fields G on a smooth manifold M can serve as a spacetime structure? In the first part of this thesis, it is found that only a severely restricted class of tensor fields can provide classical spacetime geometries, namely those that can carry predictive, interpretable and quantizable matter dynamics. The obvious dependence of this characterization of admissible tensorial spacetime geometries on specific matter is not a weakness, but rather presents an insight: it was Maxwell theory that justified Einstein to promote Lorentzian manifolds to the status of a spacetime geometry. Any matter that does not mimick the structure of Maxwell theory, will force us to choose another geometry on which the matter dynamics of interest are predictive, interpretable and quantizable. These three physical conditions on matter impose three corresponding algebraic conditions on the totally symmetric contravariant coefficient tensor field P that determines the principal symbol of the matter field equations in terms of the geometric tensor G: the tensor field P must be hyperbolic, time-orientable and energy-distinguishing. Remarkably, these physically necessary conditions on the geometry are mathematically already sufficient to realize all kinematical constructions familiar from Lorentzian geometry, for precisely the same structural reasons. This we were able to show employing a subtle interplay of convex analysis, the theory of partial differential equations and real algebraic geometry. In the second part of this thesis, we then explore general properties of any hyperbolic, time-orientable and energy-distinguishing tensorial geometry. Physically most important are the construction of freely falling non-rotating laboratories, the appearance of admissible modified dispersion relations to particular observers, and the identification of a mechanism that explains why massive particles that are faster than some massless particles can radiate off energy until they are slower than all massless particles in any hyperbolic, time-orientable and energy-distinguishing geometry. In the third part of the thesis, we explore how tensorial spacetime geometries fare when one wants to quantize particles and fields on them. This study is motivated, in part, in order to provide the tools to calculate the rate at which superluminal particles radiate off energy to become infraluminal, as explained above. Remarkably, it is again the three geometric conditions of hyperbolicity, time-orientability and energy-distinguishability that allow the quantization of general linear electrodynamics on an area metric spacetime and the quantization of massive point particles obeying any admissible dispersion relation. We explore the issue of field equations of all possible derivative order in rather systematic fashion, and prove a practically most useful theorem that determines Dirac algebras allowing the reduction of derivative orders. The final part of the thesis presents the sketch of a truly remarkable result that was obtained building on the work of the present thesis. Particularly based on the subtle duality maps between momenta and velocities in general tensorial spacetimes, it could be shown that gravitational dynamics for hyperbolic, time-orientable and energy distinguishable geometries need not be postulated, but the formidable physical problem of their construction can be reduced to a mere mathematical task: the solution of a system of homogeneous linear partial differential equations. This far-reaching physical result on modified gravity theories is a direct, but difficult to derive, outcome of the findings in the present thesis. Throughout the thesis, the abstract theory is illustrated through instructive examples.
Welche Tensorfelder G auf einer glatten Mannigfaltigkeit M können eine Raumzeit-Geometrie beschreiben? Im ersten Teil dieser Dissertation wird es gezeigt, dass nur stark eingeschränkte Klassen von Tensorfeldern eine Raumzeit-Geometrie darstellen können, nämlich Tensorfelder, die eine prädiktive, interpretierbare und quantisierbare Dynamik für Materiefelder ermöglichen. Die offensichtliche Abhängigkeit dieser Charakterisierung erlaubter tensorieller Raumzeiten von einer spezifischen Materiefelder-Dynamik ist keine Schwäche der Theorie, sondern ist letztlich genau das Prinzip, das die üblicherweise betrachteten Lorentzschen Mannigfaltigkeiten auszeichnet: diese stellen die metrische Geometrie dar, welche die Maxwellsche Elektrodynamik prädiktiv, interpretierbar und quantisierbar macht. Materiefeld-Dynamiken, welche die kausale Struktur von Maxwell-Elektrodynamik nicht respektieren, zwingen uns, eine andere Geometrie auszuwählen, auf der die Materiefelder-Dynamik aber immer noch prädiktiv, interpretierbar und quantisierbar sein muss. Diesen drei Voraussetzungen an die Materie entsprechen drei algebraische Voraussetzungen an das total symmetrische kontravariante Tensorfeld P, welches das Prinzipalpolynom der Materiefeldgleichungen (ausgedrückt durch das grundlegende Tensorfeld G) bestimmt: das Tensorfeld P muss hyperbolisch, zeitorientierbar und energie-differenzierend sein. Diese drei notwendigen Bedingungen an die Geometrie genügen, um alle aus der Lorentzschen Geometrie bekannten kinematischen Konstruktionen zu realisieren. Dies zeigen wir im ersten Teil der vorliegenden Arbeit unter Verwendung eines teilweise recht subtilen Wechselspiels zwischen konvexer Analysis, der Theorie partieller Differentialgleichungen und reeller algebraischer Geometrie. Im zweiten Teil dieser Dissertation erforschen wir allgemeine Eigenschaften aller solcher hyperbolischen, zeit-orientierbaren und energie-differenzierenden Geometrien. Physikalisch wichtig sind der Aufbau von frei fallenden und nicht rotierenden Laboratorien, das Auftreten modifizierter Energie-Impuls-Beziehungen und die Identifizierung eines Mechanismus, der erklärt, warum massive Teilchen, die sich schneller als einige masselosse Teilchen bewegen, Energie abstrahlen können, aber nur bis sie sich langsamer als alle masselossen Teilchen bewegen. Im dritten Teil der Dissertation ergründen wir die Quantisierung von Teilchen und Feldern auf tensoriellen Raumzeit-Geometrien, die die obigen physikalischen Bedingungen erfüllen. Eine wichtige Motivation dieser Untersuchung ist es, Techniken zur Berechnung der Zerfallsrate von Teilchen zu berechnen, die sich schneller als langsame masselose Teilchen bewegen. Wir finden, dass es wiederum die drei zuvor im klassischen Kontext identifizierten Voraussetzungen (der Hyperbolizität, Zeit-Orientierbarkeit und Energie-Differenzierbarkeit) sind, welche die Quantisierung allgemeiner linearer Elektrodynamik auf einer flächenmetrischen Raumzeit und die Quantizierung massiver Teilchen, die eine physikalische Energie-Impuls-Beziehung respektieren, erlauben. Wir erkunden auch systematisch, wie man Feldgleichungen aller Ableitungsordnungen generieren kann und beweisen einen Satz, der verallgemeinerte Dirac-Algebren bestimmt und die damit Reduzierung des Ableitungsgrades einer physikalischen Materiefeldgleichung ermöglicht. Der letzte Teil der vorliegenden Schrift skizziert ein bemerkenswertes Ergebnis, das mit den in dieser Dissertation dargestellten Techniken erzielt wurde. Insbesondere aufgrund der hier identifizierten dualen Abbildungen zwischen Teilchenimpulsen und -geschwindigkeiten auf allgemeinen tensoriellen Raumzeiten war es möglich zu zeigen, dass man die Gravitationsdynamik für hyperbolische, zeit-orientierbare und energie-differenzierende Geometrien nicht postulieren muss, sondern dass sich das Problem ihrer Konstruktion auf eine rein mathematische Aufgabe reduziert: die Lösung eines homogenen linearen Differentialgleichungssystems. Dieses weitreichende Ergebnis über modifizierte Gravitationstheorien ist eine direkte (aber schwer herzuleitende) Folgerung der Forschungsergebnisse dieser Dissertation. Die abstrakte Theorie dieser Doktorarbeit wird durch mehrere instruktive Beispiele illustriert.
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Horvath, Matthew Steven. "Performance Prediction of Quantization Based Automatic Target Recognition Algorithms." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1452086412.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Huang, Bihong. "Second-order prediction and residue vector quantization for video compression." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S026/document.

Повний текст джерела
Анотація:
La compression vidéo est une étape cruciale pour une grande partie des applications de télécommunication. Depuis l'avènement de la norme H.261/MPEG-2, un nouveau standard de compression vidéo est produit tous les 10 ans environ, avec un gain en compression de 50% par rapport à la précédente. L'objectif de la thèse est d'obtenir des gains en compression par rapport à la dernière norme de codage vidéo HEVC. Dans cette thèse, nous proposons trois approches pour améliorer la compression vidéo en exploitant les corrélations du résidu de prédiction intra. Une première approche basée sur l'utilisation de résidus précédemment décodés montre que, si des gains sont théoriquement possibles, le surcoût de la signalisation les réduit pratiquement à néant. Une deuxième approche basée sur la quantification vectorielle mode-dépendent (MDVQ) du résidu préalablement à l'étape classique transformée-quantification scalaire, permet d'obtenir des gains substantiels. Nous montrons que cette approche est réaliste, car les dictionnaires sont indépendants du QP et de petite taille. Enfin, une troisième approche propose de rendre adaptatif les dictionnaires utilisés en MDVQ. Un gain substantiel est apporté par l'adaptivité, surtout lorsque le contenu vidéo est atypique, tandis que la complexité de décodage reste bien contenue. Au final on obtient un compromis gain-complexité compatible avec une soumission en normalisation
Video compression has become a mandatory step in a wide range of digital video applications. Since the development of the block-based hybrid coding approach in the H.261/MPEG-2 standard, new coding standard was ratified every ten years and each new standard achieved approximately 50% bit rate reduction compared to its predecessor without sacrificing the picture quality. However, due to the ever-increasing bit rate required for the transmission of HD and Beyond-HD formats within a limited bandwidth, there is always a requirement to develop new video compression technologies which provide higher coding efficiency than the current HEVC video coding standard. In this thesis, we proposed three approaches to improve the intra coding efficiency of the HEVC standard by exploiting the correlation of intra prediction residue. A first approach based on the use of previously decoded residue shows that even though gains are theoretically possible, the extra cost of signaling could negate the benefit of residual prediction. A second approach based on Mode Dependent Vector Quantization (MDVQ) prior to the conventional transformed scalar quantization step provides significant coding gains. We show that this approach is realistic because the dictionaries are independent of QP and of a reasonable size. Finally, a third approach is developed to modify dictionaries gradually to adapt to the intra prediction residue. A substantial gain is provided by the adaptivity, especially when the video content is atypical, without increasing the decoding complexity. In the end we get a compromise of complexity and gain for a submission in standardization
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Vasconcelos, Nuno Miguel Borges de Pinho Cruz de. "Library-based image coding using vector quantization of the prediction space." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/62918.

Повний текст джерела
Анотація:
Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1993.
Includes bibliographical references (leaves 122-126).
by Nuno Miguel Borges de Pinho Cruz de Vasconcelos.
M.S.
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Boland, Simon Daniel. "High quality audio coding using the wavelet transform." Thesis, Queensland University of Technology, 1998.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Clayton, Arnshea. "The Relative Importance of Input Encoding and Learning Methodology on Protein Secondary Structure Prediction." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_theses/19.

Повний текст джерела
Анотація:
In this thesis the relative importance of input encoding and learning algorithm on protein secondary structure prediction is explored. A novel input encoding, based on multidimensional scaling applied to a recently published amino acid substitution matrix, is developed and shown to be superior to an arbitrary input encoding. Both decimal valued and binary input encodings are compared. Two neural network learning algorithms, Resilient Propagation and Learning Vector Quantization, which have not previously been applied to the problem of protein secondary structure prediction, are examined. Input encoding is shown to have a greater impact on prediction accuracy than learning methodology with a binary input encoding providing the highest training and test set prediction accuracy.
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Kamath, Vidya P. "Enhancing Gene Expression Signatures in Cancer Prediction Models: Understanding and Managing Classification Complexity." Scholar Commons, 2010. http://scholarcommons.usf.edu/etd/3653.

Повний текст джерела
Анотація:
Cancer can develop through a series of genetic events in combination with external influential factors that alter the progression of the disease. Gene expression studies are designed to provide an enhanced understanding of the progression of cancer and to develop clinically relevant biomarkers of disease, prognosis and response to treatment. One of the main aims of microarray gene expression analyses is to develop signatures that are highly predictive of specific biological states, such as the molecular stage of cancer. This dissertation analyzes the classification complexity inherent in gene expression studies, proposing both techniques for measuring complexity and algorithms for reducing this complexity. Classifier algorithms that generate predictive signatures of cancer models must generalize to independent datasets for successful translation to clinical practice. The predictive performance of classifier models is shown to be dependent on the inherent complexity of the gene expression data. Three specific quantitative measures of classification complexity are proposed and one measure ( f) is shown to correlate highly (R 2=0.82) with classifier accuracy in experimental data. Three quantization methods are proposed to enhance contrast in gene expression data and reduce classification complexity. The accuracy for cancer prognosis prediction is shown to improve using quantization in two datasets studied: from 67% to 90% in lung cancer and from 56% to 68% in colorectal cancer. A corresponding reduction in classification complexity is also observed. A random subspace based multivariable feature selection approach using costsensitive analysis is proposed to model the underlying heterogeneous cancer biology and address complexity due to multiple molecular pathways and unbalanced distribution of samples into classes. The technique is shown to be more accurate than the univariate ttest method. The classifier accuracy improves from 56% to 68% for colorectal cancer prognosis prediction.  A published gene expression signature to predict radiosensitivity of tumor cells is augmented with clinical indicators to enhance modeling of the data and represent the underlying biology more closely. Statistical tests and experiments indicate that the improvement in the model fit is a result of modeling the underlying biology rather than statistical over-fitting of the data, thereby accommodating classification complexity through the use of additional variables.
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Книги з теми "Predictive quantization"

1

So, Kevin Kin Man. A new quantization technique for linear predictive speech coding. Manchester: University of Manchester, 1994.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Robust Source Coding of Images With Predictive Trellis - Coded Quantization. Storming Media, 1996.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Conditional entropy-constrained residual VQ with application to image coding. [Washington, DC: National Aeronautics and Space Administration, 1996.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

C, Chung Wilson, Smith Mark J. T, and United States. National Aeronautics and Space Administration., eds. Conditional entropy-constrained residual VQ with application to image coding. [Washington, DC: National Aeronautics and Space Administration, 1996.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

C, Chung Wilson, Smith Mark J. T, and United States. National Aeronautics and Space Administration., eds. Conditional entropy-constrained residual VQ with application to image coding. [Washington, DC: National Aeronautics and Space Administration, 1996.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

C, Chung Wilson, Smith Mark J. T, and United States. National Aeronautics and Space Administration., eds. Conditional entropy-constrained residual VQ with application to image coding. [Washington, DC: National Aeronautics and Space Administration, 1996.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Частини книг з теми "Predictive quantization"

1

Gersho, Allen, and Robert M. Gray. "Predictive Quantization." In Vector Quantization and Signal Compression, 203–23. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3626-0_7.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Gersho, Allen, and Robert M. Gray. "Predictive Vector Quantization." In Vector Quantization and Signal Compression, 487–517. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3626-0_13.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Sun, Zhen, Yue-Nan Li, and Zhe-Ming Lu. "Side-Match Predictive Vector Quantization." In Lecture Notes in Computer Science, 405–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11553939_58.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Goodwin, Graham C., Jan Østergaard, Daniel E. Quevedo, and Arie Feuer. "A Vector Quantization Approach to Scenario Generation for Stochastic NMPC." In Nonlinear Model Predictive Control, 235–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01094-1_19.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Bhaskar, Udaya. "Adaptive Predictive Coding with Transform Domain Quantization." In Speech and Audio Coding for Wireless and Network Applications, 265–69. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-3232-3_34.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Andersen, Søren Vang, Søren Holdt Jensen, and Egon Hansen. "Vector-Predictive Speech Coding with Quantization Noise Modelling." In Signal Analysis and Prediction, 429–42. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-1768-8_30.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Yakut, Mehmet. "Multiscale Image Representation Using Switched Codebook Predictive Vector Quantization." In Proceedings of The 17th International Symposium on Computer and Information Sciences, 86–90. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9780429332821-20.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Shi, Min, and Shengli Xie. "A New Predictive Vector Quantization Method Using a Smaller Codebook." In Lecture Notes in Computer Science, 229–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11539087_28.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Hirose, Akira, and Tomoyuki Nagashima. "Predictive Self-Organizing Map for Vector Quantization of Migratory Signals." In Artificial Neural Networks — ICANN 2002, 884–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-46084-5_143.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Gersho, Allen, and Robert M. Gray. "Linear Prediction." In Vector Quantization and Signal Compression, 83–129. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3626-0_4.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Тези доповідей конференцій з теми "Predictive quantization"

1

Rizvi, Syed A., Lin-Cheng Wang, and Nasser M. Nasrabadi. "Entropy-constrained predictive residual vector quantization." In Photonics East '95, edited by Raghuveer M. Rao, Soheil A. Dianat, Steven W. McLaughlin, and Martin Hassner. SPIE, 1995. http://dx.doi.org/10.1117/12.228223.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Rizvi, Syed A., Nasser M. Nasrabadi, and Lin-Cheng Wang. "Variable-rate predictive residual vector quantization." In Visual Communications and Image Processing '95, edited by Lance T. Wu. SPIE, 1995. http://dx.doi.org/10.1117/12.206758.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Hashemi, Mahmoud R., Tet H. Yeap, and Sethuraman Panchanathan. "Predictive vector quantization using neural networks." In Electronic Imaging '97, edited by Nasser M. Nasrabadi and Aggelos K. Katsaggelos. SPIE, 1997. http://dx.doi.org/10.1117/12.269776.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Narayan, Ajai, and Tenkasi V. Ramabadran. "Image coding through predictive vector quantization." In San Diego '92, edited by Andrew G. Tescher. SPIE, 1993. http://dx.doi.org/10.1117/12.139093.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Desappan, Kumar, Mihir Mody, Manu Mathew, Pramod Swami, and Praveen Eppa. "CNN Inference: Dynamic and Predictive Quantization." In 2018 IEEE 8th International Conference on Consumer Electronics - Berlin. IEEE, 2018. http://dx.doi.org/10.1109/icce-berlin.2018.8576251.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Chen, Yuepeng, Jingxin Zhang, Shenpeng Li, and Li Chai. "Robust H∞ optimal signal predictive quantization." In 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC). IEEE, 2009. http://dx.doi.org/10.1109/cdc.2009.5400725.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Kyeong Ho Yang, Wenwu Zhu, and A. F. Faryar. "Perceptual quantization for predictive coding of images." In Proceedings of 6th International Conference on Image Processing (ICIP'99). IEEE, 1999. http://dx.doi.org/10.1109/icip.1999.822922.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Mohsenian, N., and N. M. Nasrabadi. "Predictive vector quantization using a neural network." In Proceedings of ICASSP '93. IEEE, 1993. http://dx.doi.org/10.1109/icassp.1993.319793.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Mohsenian, Nader, and Nasser M. Nasrabadi. "Neural net approach to predictive vector quantization." In Applications in Optical Science and Engineering, edited by Petros Maragos. SPIE, 1992. http://dx.doi.org/10.1117/12.131465.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Gollin, Nicola, Michele Martone, Michelangelo Villano, Paola Rizzoli, and Gerhard Krieger. "Predictive Quantization for Staggered Synthetic Aperture Radar." In 2019 12th German Microwave Conference (GeMiC). IEEE, 2019. http://dx.doi.org/10.23919/gemic.2019.8698197.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Звіти організацій з теми "Predictive quantization"

1

Marvel, Lisa M. Robust Source Coding of Images With Predictive Trellis - Coded Quantization. Fort Belvoir, VA: Defense Technical Information Center, September 1996. http://dx.doi.org/10.21236/ada315312.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Також вас можуть зацікавити розширені добірки на тему "Predictive quantization" для конкретних типів джерел:
Статті в журналах Дисертації
Ми пропонуємо знижки на всі преміум-плани для авторів, чиї праці увійшли до тематичних добірок літератури. Зв'яжіться з нами, щоб отримати унікальний промокод!

До бібліографії