Conferences related to Basis algorithms

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2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


2021 IEEE Photovoltaic Specialists Conference (PVSC)

Photovoltaic materials, devices, systems and related science and technology


ICC 2021 - IEEE International Conference on Communications

IEEE ICC is one of the two flagship IEEE conferences in the field of communications; Montreal is to host this conference in 2021. Each annual IEEE ICC conference typically attracts approximately 1,500-2,000 attendees, and will present over 1,000 research works over its duration. As well as being an opportunity to share pioneering research ideas and developments, the conference is also an excellent networking and publicity event, giving the opportunity for businesses and clients to link together, and presenting the scope for companies to publicize themselves and their products among the leaders of communications industries from all over the world.


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


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Periodicals related to Basis algorithms

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems II: Express Briefs, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


Communications Letters, IEEE

Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)


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Most published Xplore authors for Basis algorithms

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Xplore Articles related to Basis algorithms

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Selection of the best wavelet basis for a time-varying Volterra model

Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154), 2000

To enable identification of a time-varying Volterra model using a single input/output realisation, sequences from an orthonormal basis are used to approximate the time-variation. Our work concerns the choice of sequences from a library which comprises several bases. Using a library of wavelet packets allows the use of the best basis algorithm. We apply the best basis algorithm in order ...


Best basis algorithm for orthonormal shift-invariant trigonometric decomposition

1996 IEEE Digital Signal Processing Workshop Proceedings, 1996

Adaptive signal representations in overcomplete libraries of waveforms have been widely used. The local cosine decomposition of Coifman and Wickerhauser (see IEEE Trans. Inf. Th., vol.38, no.3, p.713-18, 1992) is modified by incorporating two degrees of freedom that increase the adaptability of the best basis. These are relative shifts between resolution levels and adaptive polarity foldings. The resultant expansion is ...


Dysphonic voice classification using wavelet packet transform and artificial neural network

Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439), 2003

In [Schuck Jr. and Parraga, 2002] work, it was demonstrated the viability of the wavelet packet transform (WP) and the best basis algorithm (BBA) as a feature extractor (FE) for a dysphonic voice classification systems. It was shown the better choices of wavelet and cost functions were Symlet 5 and Shannon entropy. Also, a linear discriminator between normal and dysphonic ...


Chain-block algorithm to RVM on large scale problems

2009 2nd IEEE International Conference on Computer Science and Information Technology, 2009

RVM enables sparse classification and regression functions to be obtained by linearly-weighting a small number of fixed basis functions from a large dictionary of potential candidates.TOA on RVM has O(M<sup>3</sup>) time and O(M<sup>2</sup>) space complexity, where M is the training set size. It is thus computationally infeasible on very large data sets. We propose CBA . it decomposed large datasets ...


Adaptive object-based image compression using wavelet packets

International Symposium on VIPromCom Video/Image Processing and Multimedia Communications, 2002

In this work we discuss an object-based wavelet image coding system which employs the wavelet packet best basis algorithm to adapt to each object separately. In addition to the increased functionality inherent to any object- based codec, the enhanced rate-distortion performance for images exhibiting objects with different frequency properties is shown.


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Educational Resources on Basis algorithms

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IEEE.tv Videos

Overcoming the Static Learning Bottleneck - the Need for Adaptive Neural Learning - Craig Vineyard: 2016 International Conference on Rebooting Computing
Walter J Freeman and Robert Kozma - Physical Basis of Intelligence
26th Annual MTT-AP Symposium and Mini Show - Krishna Raghunandan
IMS 2015: Four scientists who saved Maxwells Theory
IMS 2012 Microapps - Custom OFDM Validation of Wireless/Military DSP Algorithms and RF Components Daren McClearnon, Jin-Biao Xu, Agilent EEsof
Cultural Algorithms: Harnessing the Power of Social Intelligence 1
Julian Togelius: Algorithms That Play & Design Games
IEEE Robert N. Noyce Medal - Tsugio Makimoto - 2018 IEEE Honors Ceremony
IoT Security Best Practices - Webinar by George Corser and Jared Bielby
Brain Panelist - Jack Gallant: 2016 Technology Time Machine
Optimization Algorithms for Signal Processing
Cultural Algorithms: Harnessing the Power of Social Intelligence 2
Comparing Partitions from Clustering Algorithms
Richard Nute, D. Ray Corson, Jim Barrick - IEEE Medal for Environmental and Safety Technologies, 2019 IEEE Honors Ceremony
Roberto Padovani accepts the IEEE Alexander Graham Bell Medal - Honors Ceremony 2016
Life Through the Eyes of a Machine
IEEE Alexander Graham Bell - Nambi Seshadri - 2018 IEEE Honors Ceremony
IEEE Expert Now
Some Thoughts on a Gap Between Theory and Practice of Evolutionary Algorithms - WCCI 2012
Spiking Network Algorithms for Scientific Computing - William Severa: 2016 International Conference on Rebooting Computing

IEEE-USA E-Books

  • Selection of the best wavelet basis for a time-varying Volterra model

    To enable identification of a time-varying Volterra model using a single input/output realisation, sequences from an orthonormal basis are used to approximate the time-variation. Our work concerns the choice of sequences from a library which comprises several bases. Using a library of wavelet packets allows the use of the best basis algorithm. We apply the best basis algorithm in order to select the wavelet packets for approximating the true system's time-variation in the model. The minimum entropy criterion determines the most efficient basis approximation enabling a minimum number of sequences to be used, leading to a more parsimonious model.

  • Best basis algorithm for orthonormal shift-invariant trigonometric decomposition

    Adaptive signal representations in overcomplete libraries of waveforms have been widely used. The local cosine decomposition of Coifman and Wickerhauser (see IEEE Trans. Inf. Th., vol.38, no.3, p.713-18, 1992) is modified by incorporating two degrees of freedom that increase the adaptability of the best basis. These are relative shifts between resolution levels and adaptive polarity foldings. The resultant expansion is shift-invariant, and yields adaptive time-frequency distributions which are characterized by high resolution, high concentration and suppressed cross-terms associated with the Wigner distribution.

  • Dysphonic voice classification using wavelet packet transform and artificial neural network

    In [Schuck Jr. and Parraga, 2002] work, it was demonstrated the viability of the wavelet packet transform (WP) and the best basis algorithm (BBA) as a feature extractor (FE) for a dysphonic voice classification systems. It was shown the better choices of wavelet and cost functions were Symlet 5 and Shannon entropy. Also, a linear discriminator between normal and dysphonic voices was performed. This work present the use an artificial neural network (ANN) in addition to WP and BBA to perform a non-linear discriminator. The WP with 5 dilatation levels and BBA of the sustained vowel /a/ of 13 normal and 51 dysphonic previously diagnosed subjects were performed. Then the entropy values of each best tree's nodes were used for the classification. A ANN was designed with 3 layers ( 4 neurones in the hidden layer and 2 in the last layer). The non-linear function was hyperbolic tangent. The ANN was trained using backpropagation with a group of 6 normal and 21 dysphonic subjects chose at random from the database. Then, all the 61 subjects were classified. The system had a success rate 84.3%, with 4.6% of false negatives and 10.9% false positives.

  • Chain-block algorithm to RVM on large scale problems

    RVM enables sparse classification and regression functions to be obtained by linearly-weighting a small number of fixed basis functions from a large dictionary of potential candidates.TOA on RVM has O(M<sup>3</sup>) time and O(M<sup>2</sup>) space complexity, where M is the training set size. It is thus computationally infeasible on very large data sets. We propose CBA . it decomposed large datasets to subdata blocks by sampled homogeneously and getted solution by chain iteration taking TOA as basis algorithm. Regression experiments with synthetical large sbenchmark data set demonstrates CBA yielded state-of-the-art performance: its time complexity is linear in M and space complexity is independent of M, keeping high accuracy and sparsity at the same time. Document shows that CBA is also much better than TFA on time complexity and sparsity.

  • Adaptive object-based image compression using wavelet packets

    In this work we discuss an object-based wavelet image coding system which employs the wavelet packet best basis algorithm to adapt to each object separately. In addition to the increased functionality inherent to any object- based codec, the enhanced rate-distortion performance for images exhibiting objects with different frequency properties is shown.

  • Expanding a behavioral repertoire by tuning spinal primitives

    Work in the frog spinal cord, and more recently in mammals, suggests that the degrees of freedom problem in motor planning may be simplified by building motor actions from combinations of motor primitives. How motor primitives arise from spinal circuits, their properties and their plasticity are important issues for this framework. Most recently, we have used various decomposition techniques (independent components analysis, matching pursuit cosine packet analysis, best basis algorithm and wavelet methods) in both simple and complex behaviors to examine the muscles that are controlled as groups or units, and to investigate the pattern and time scale of action of primitives in behaviors. Our data are beginning to provide a description of the way in which spinal elements are controlled for incorporation into more complex behaviors. We outline this description and our methods in this paper.

  • Optimized local discriminant basis algorithm

    Local discriminant bases method is a powerful algorithmic framework for feature extraction and classification applications that is based on supervised training. It is considerably faster compared to more theoretically ideal feature extraction methods such as principal component analysis or projection pursuit. In this paper an optimization block is added to the original local discriminant bases algorithm to promote the difference between disjoint signal classes. This is done by optimally weighting the local discriminant basis using the steepest decent algorithm. The proposed method is particularly useful when background features in the signal space show strong correlation with regions of interest in the signal as in mammograms for instance.

  • Primeness notions in multidimensional systems theory

    Different characterizations of primeness of polynomial matrices that are mutually equivalent in the case of univariate polynomials lead to various primeness concepts in the multivariate situation. This fact gives rise to a more refined view to observability and controllability of multidimensional systems. Algorithms for testing primeness properties are given based on computer algebraic techniques.

  • Decoding of convolutional codes using a syndrome trellis

    Soft-decision maximum-likelihood decoding of convolutional codes using the Viterbi algorithm with a syndrome trellis is proposed. The parity check matrix of a convolutional code is used to construct the trellis. This trellis is minimal. The number of operations for the decoding of one block of a q-ary rate k/n convolutional code is /spl sim/nq/sup min(k,n-k)/q/sup /spl nu//, where /spl nu/ is the memory size of the code. When the code rate satisfies k/n> 1/2 , the proposed algorithm is simpler than the classical Viterbi algorithm that has complexity /spl sim/nq/sup k/q/sup /spl nu//.<<ETX>>

  • Fast Variants of the Backward-Oracle-Marching Algorithm

    This study focuses on the faster exact single pattern string matching algorithms. In all solutions, two variants of BOM, EBOM and FBOM are very efficient. We improved them and presented two algorithms named Simplified-EBOM and Simplified-FBOM through removing the unnecessary branches and accomplishing the core calculation of the algorithm in a 1-dimensional array. The experimental results indicated that Simplified-EBOM is fast for short patterns and it is 12% faster than its basis algorithm on average.



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