Rozprawy doktorskie na temat „Minimum Classification Error algorithm”
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Wang, Xuechuan, i n/a. "Feature Extraction and Dimensionality Reduction in Pattern Recognition and Their Application in Speech Recognition". Griffith University. School of Microelectronic Engineering, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030619.162803.
Pełny tekst źródłaWang, Xuechuan. "Feature Extraction and Dimensionality Reduction in Pattern Recognition and Their Application in Speech Recognition". Thesis, Griffith University, 2003. http://hdl.handle.net/10072/365680.
Pełny tekst źródłaThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Microelectronic Engineering
Full Text
Han, Seungju. "A family of minimum Renyi's error entropy algorithm for information processing". [Gainesville, Fla.] : University of Florida, 2007. http://purl.fcla.edu/fcla/etd/UFE0021428.
Pełny tekst źródłaFu, Qiang. "A generalization of the minimum classification error (MCE) training method for speech recognition and detection". Diss., Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22705.
Pełny tekst źródłaAlbarakati, Noor. "FAST NEURAL NETWORK ALGORITHM FOR SOLVING CLASSIFICATION TASKS". VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/2740.
Pełny tekst źródłaChen, Nan. "An IEEE 802.15.4 Packet Error Classification Algorithm : Discriminating Between Multipath Fading and Attenuation and WLAN". Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-24918.
Pełny tekst źródłaKunert, Gerd. "Anisotropic mesh construction and error estimation in the finite element method". Universitätsbibliothek Chemnitz, 2000. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200000033.
Pełny tekst źródłaShin, Sung-Hwan. "Objective-driven discriminative training and adaptation based on an MCE criterion for speech recognition and detection". Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50255.
Pełny tekst źródłaDu, Zekun. "Algorithm Design and Optimization of Convolutional Neural Networks Implemented on FPGAs". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254575.
Pełny tekst źródłaDeep learning har utvecklats snabbt under den senaste tiden. Det har funnit applikationer inom många områden, som är huvudfälten inom Artificial Intelligence. Kombinationen av Deep Learning och innbyggda system är en god inriktning i det tekniska fältet. Syftet med detta projekt är att designa en Deep Learning-baserad Neural Network algoritm som kan implementeras på hårdvara, till exempel en FPGA. Projektet är baserat på modern forskning inom Deep Learning Neural Networks samt hårdvaruegenskaper.Systemet är baserat på PyTorch och CUDA. Projektets fokus är bild klassificering baserat på Convolutional Neural Networks (CNN). Det finns många bra CNN modeller att studera, t.ex. ResNet, ResNeXt och MobileNet. Genom att applicera dessa modeller till designen valdes en algoritm med MobileNetmodellen. Valet av modell är baserat på faktorer så som antal flyttalsoperationer, antal modellparametrar och klassifikationsprecision. Den mjukvarubaserade versionen av den MobileNet-baserade algoritmen har top-1 error på 5.5En hårdvarusimulering av MobileNet nätverket designades, i vilket parametrarna är konverterade från flyttal till 8-bit heltal. Talen från varje lager klipps till fixed-bit heltal för att anpassa nätverket till befintliga hårdvarubegränsningar. En metod designas för att simulera talförändringen på hårdvaran. Baserat på denna simuleringsmetod reduceras top-1 error till 12.3
Palkki, Ryan D. "Chemical identification under a poisson model for Raman spectroscopy". Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/45935.
Pełny tekst źródłaChallakere, Nagaravind. "Carrier Frequency Offset Estimation for Orthogonal Frequency Division Multiplexing". DigitalCommons@USU, 2012. https://digitalcommons.usu.edu/etd/1423.
Pełny tekst źródłaKunert, Gerd. "A note on the energy norm for a singularly perturbed model problem". Universitätsbibliothek Chemnitz, 2001. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200100062.
Pełny tekst źródłaNieuwoudt, Christoph. "Cross-language acoustic adaptation for automatic speech recognition". Thesis, Pretoria : [s.n.], 2000. http://upetd.up.ac.za/thesis/available/etd-01062005-071829.
Pełny tekst źródłaKahaei, Mohammad Hossein. "Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes". Thesis, Queensland University of Technology, 1998. https://eprints.qut.edu.au/36044/7/36044_Digitised_Thesis.pdf.
Pełny tekst źródłaGrosman, Sergey. "Adaptivity in anisotropic finite element calculations". Doctoral thesis, Universitätsbibliothek Chemnitz, 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200600815.
Pełny tekst źródłaIrmer, Ralf. "Multiuser Transmission in Code Division Multiple Access Mobile Communications Systems". Doctoral thesis, Technische Universität Dresden, 2004. https://tud.qucosa.de/id/qucosa%3A24546.
Pełny tekst źródłaDer codegeteilte Mehrfachzugriff (CDMA) wird bei allen zellularen Mobilfunksystemen der dritten Generation verwendet und ist ein aussichtsreicher Kandidat für zukünftige Technologien. Die Netzkapazität, also die Anzahl der Nutzer je Funkzelle, ist durch auftretende Interferenzen zwischen den Nutzern begrenzt. Für die Aufwärtsstrecke von den mobilen Endgeräten zur Basisstation können die Interferenzen durch Verfahren der Mehrnutzerdetektion im Empfänger verringert werden. Für die Abwärtsstrecke, die höhere Datenraten bei Multimedia-Anwendungen transportiert, kann das Sendesignal im Sender so vorverzerrt werden, dass der Einfluß der Interferenzen minimiert wird. Die informationstheoretische Motivation liefert dazu das Writing-on-Dirty-Paper Theorem. Das Signal-zu-Rausch-Verhältnis ist ein geeignetes Kriterium für die Performanz in rauschdominierten Szenarien. Mit Sende- und Empfangsfiltern kann das SNR durch den vorgeschlagenen Eigenprecoder maximiert werden. Durch den Einsatz von Mehrfachantennen im Sender und Empfänger kann die Performanz signifikant erhöht werden. Mit dem Generalized Selection MIMO Eigenprecoder können Transceiver mit reduzierter Komplexität ermöglicht werden. Sowohl für den Empfänger als auch für den Sender existieren Methoden, die Interferenzen vollständig zu eliminieren, oder den mittleren quadratischen Fehler zu minimieren. Der Maximum-Likelihood-Empfänger minimiert die Bitfehlerwahrscheinlichkeit (BER), hat jedoch kein entsprechendes Gegenstück im Sender. Die in dieser Arbeit vorgeschlagene Minimum Bit Error Rate Multiuser Transmission (TxMinBer) minimiert die BER am Detektor durch Sendesignalverarbeitung. Dieses nichtlineare Verfahren nutzt die Kenntnis der Datensymbole und des Mobilfunkkanals, um ein Sendesignal zu generieren, dass die BER unter Berücksichtigung einer Sendeleistungsnebenbedingung minimiert. Dabei werden nichtlineare Optimierungsverfahren wie Sequentielle Quadratische Programmierung (SQP) verwendet. Die Performanz linearer und nichtlinearer MUT-Verfahren MUT-Algorithmen mit linearen Empfängern wird am Beispiel des TD-SCDMA-Standards verglichen. Das Problem der Interferenzen kann mit allen untersuchten Verfahren gelöst werden, die TxMinBer-Methode benötigt jedoch die geringste Sendeleistung, um eine bestimmt Anzahl von Nutzern zu unterstützen. Die hohe Rechenkomplexität der MUT-Algorithmen ist ein wichtiges Problem bei der Implementierung in Real-Zeit-Systemen. Durch die Ausnutzung von Struktureigenschaften der Systemmatrizen kann die Komplexität der linearen MUT-Verfahren signifikant reduziert werden. Verschiedene Verfahren zur Invertierung der Systemmatrizen werden aufgezeigt und verglichen. Es werden Vorschläge gemacht, die Komplexität der Minimum Bit Error Rate Multiuser Transmission zu reduzieren, u.a. durch Vermeidung der Sendeleistungsnebenbedingung durch eine Beschränkung der Optimierung auf die Phasen des Sendesignalvektors. Die Komplexität der nichtlinearen Methoden ist um einige Größenordungen höher als die der linearen Verfahren. Weitere Forschungsanstrengungen an diesem Thema sowie die wachsende Rechenleistung von integrierten Halbleitern werden künftig die Ausnutzung der besseren Leistungsfähigkeit der nichtlinearen MUT-Verfahren erlauben.
Chang, Yung-Di, i 張詠棣. "Chip Design of Memory-Based Architecture for Minimum Classification Error". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/02852597645232023458.
Pełny tekst źródła國立暨南國際大學
電機工程學系
98
This thesis proposed a minimum classification error (MCE) processor. The well characteristic of MCE is to retrain data for each group, such that the distance between group and group is pulled farther. MCE can improve recognition rate and reduce misrecognition, so MCE is widely applied to speech processing and image processing. Besides, MCE is also applied to hand writing, face detection, and neural network, etc. This MCE processor is, in our knowledge, the first proposed chip design. It is also the main contribution of this thesis. Due to the MCE algorithm includes vector operation, matrix operation, exponent function, natural logarithm function, sigmoid function, square root function, and also needs iteration, we adopted In-Place Mode of memory architecture, and used look-up table (LUT) to map functions. The memory-based architecture MCE processor is synthesized by UMC 90nm standard cell library. The input format of the MCE processor is 24 bits, and the area is approximately 8.07mm2. The power consumption is approximately 3.6393mW. The maximum operating frequency is 83MHz.
Chu, Ying-Lin, i 朱映霖. "SPEAKER IDENTIFICATION BASED ON AN IMPROVED MINIMUM CLASSIFICATION ERROR METHOD". Thesis, 2007. http://ndltd.ncl.edu.tw/handle/52761181230782785251.
Pełny tekst źródła國立中央大學
電機工程研究所
95
In speaker recognition, it is important to have effective training data to train speaker models which have a great effect on recognition performance. In abundant training data, traditional speaker models which is based on maximum likelihood have a good effect, but it is opposite in slight training data. Besides, being independent with other speakers, we used training data for the same speaker to train speaker model owning to the method of maximum likelihood. In the stage of training model, we did not concern the relation of different speaker model, so we would get confused easily in speaker recognition. In recent years, Discriminative Acoustic Model Training is proposed to minimize classification error, not maximizing training acoustic models likelihood. In this thesis, we use minimum classification error to train speaker models, and support vector machines to improve minimum classification error. Due to the non-robustness of minimum classification error in setup for the amount of competitive speakers, we use the scores of speaker models for training data as labels of classes to train support vector machines. Then, we use support vectors to choose competitive speakers to make more robust and higher speaker recognition performance than minimum classification error.
"Parametric classification and variable selection by the minimum integrated squared error criterion". Thesis, 2012. http://hdl.handle.net/1911/70219.
Pełny tekst źródłaHung, Tsz-Ying, i 洪慈霙. "Matrix-Type Minimum Classification Error Based Two-Dimension Cepstrum for Speech Recognition". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/71026177856492665602.
Pełny tekst źródła國立暨南國際大學
電機工程學系
98
The thesis is investigated into training models of matrix-type minimum classification error (MMCE) to compare with other ways, and used different methods of enhancement to improve the performance in the speech recognition system. For using the method of minimum classification error on the special dimension, we propose matrix-type minimum classification error. The feature extraction bases on Modified Two-Dimension Cepstrum (MTDC), and template matching employs Gaussian Mixture Models (GMM). However, the noisy background in our life may interfere with the performance. Hence, we adopt matrix-type minimum classification(MMCE) to enhance speech features. Next, we used the system to identify the speech. We adopted numbers in Chinese (0-9) from 10 speakers (5 males and 5 females), then everyone chanted 10 times for each number (total files: 10400). We selected 980 files of each one as the training file, the remainder as the testing files. Finally, we compared and discussed the results which are tested in several variable background noises form different conditions.
Huang, Chun-Chieh, i 黃俊傑. "Maximum Likelihood and Minimum Classification Error Beam-forming for Robust Speech Recognition". Thesis, 2008. http://ndltd.ncl.edu.tw/handle/p8n75s.
Pełny tekst źródła國立臺北科技大學
電腦與通訊研究所
96
The paper discusses the approach to improve the speech recognition in the far speaking environment by the array signal process. Because the speech signal became distorted and the adding noise, it will degrade the recognizable rate. The microphone array can improve the quality of the speech record. The traditional array process focuses on increasing the signal to noise ratio or robust signal by the some constrains. But these methods ignore the operation principle of the speech recognizer. The robust speech signal wave can’t correspond to the well recognizable rate. The paper provides the array process don’t only improve the signal wave but also utilize the statistics property of the hidden Markov model, HMM widely used in the speech recognition. Adjusting the microphone array filter parameters practices the Maximum Likelihood algorithm in microphone array and this method has been suggested. It will increase the likelihood with the supervised sentence. Lastly, the paper provides the minimum classification error algorithm in the array process. The approach reduces the loss function with corresponding the classification error by adjusting the frequency response of the array. So we will utilize the feedback between the speech recognizer and the array to improve the speech recognition accuracy. The simulative speech signal experiments have finished. The ML will provide the better performance than the traditional Delay and Sum algorithm. The MCE algorithm will advance the recognition accuracy than ML algorithm.
Hsieh, Ping-Ju, i 謝秉儒. "Optimal Design of Minimum Mean-Square Error Noise Reduction Algorithm Using Simulated Annealing Technique". Thesis, 2008. http://ndltd.ncl.edu.tw/handle/75286118336700183998.
Pełny tekst źródła國立交通大學
機械工程系所
96
This paper proposes an optimized speech enhancement algorithm aimed at single-channel noise reduction (NR). The optimization process is based on an objective function obtained in a regression model and the simulated annealing (SA) algorithm that is well suited for problems with many local optima. The NR algorithm, minimum mean-square error noise reduction (MMSE-NR) algorithm, employs a time-recursive averaging (TRA) method for noise estimation. It was found in a sensitivity analysis that one of the two optimal parameters remains relatively constant, while the other parameter varies drastically in different noise scenarios. Another NR algorithm proposed in the paper employs linear prediction coding (LPC) as a preprocessor for extracting the correlated portion of human speech. Objective and subjective tests were undertaken to compare the optimized MMSE-TRA-NR algorithm with several conventional NR algorithms. White noise and car noise at signal-to-noise ratio (SNR) 5 dB are used in these tests. The results of subjective test were processed by using analysis of variance (ANOVA) to justify the statistic significance. A post-hoc test (Tukey’s HSD) was conducted to assess the statistical difference between the NR algorithms. As compared to conventional algorithms, the optimized MMSE-TRA-NR algorithm proved effective in enhancing noise-corrupted speech signals, without compromising the timbral quality.
Wang, Chien-Shun, i 王建順. "A Novel Color Interpolation Algorithm and Hardware Architecture by Pre-estimating Minimum Square Error". Thesis, 2005. http://ndltd.ncl.edu.tw/handle/43359896324429417896.
Pełny tekst źródła國立成功大學
電機工程學系碩博士班
93
In recent years, digital still cameras (DSCs) are becoming very popular consumer electronic devices. Most digital still cameras use single Charge-Coupled Device (CCD) with Color Filter Array (CFA) to capture sub-sampled digital color images. In this thesis, a novel color interpolation algorithm for Color Filter Array (CFA) in digital still cameras (DSCs) is presented. This work introduces pre-estimating the minimum square error to address the color interpolation for CFA. In order to estimate the missing pixels in Bayer CFA pattern, the weights of adjacent color pattern pairs are decided by the matrix computation. We adopt the color model (KR, KB) used in many color interpolation algorithms for CFA. The proposed algorithm can achieve better performance shown in the experimental results. Comparing the previous methods, the proposed color interpolation algorithm can provide high quality image in DSCs and regular architecture for VLSI design. For the purpose of the efficient hardware implementation, we propose a modified recursive Schur algorithm for hardware design of the proposed interpolation Algorithm.
Lin, Jheng-Yao, i 林政曜. "Utilizing Minimum Mean-Square-Error algorithm and Kalman Filter for channel estimation in Orthogonal Frequency-Division Multiplexing system". Thesis, 2004. http://ndltd.ncl.edu.tw/handle/94895513978379800505.
Pełny tekst źródła淡江大學
電機工程學系碩士班
94
In this report, the channel frequency response of the wireless Orthogonal Frequency-Division Multiplexing system has been estimated and modeled by utilizing the minimum mean-square-error (MSE) algorithm and kalman filtering algorithm. Two channel models have been developed for the system considered, namely, an additive white Gaussian noise only channel and a Rayleigh slow-fading channel with white Gaussian noise added channel. With the models developed several examples have been simulated to study the resulting system symbol error rates vs. signal to noise ratios and fading factors to study the effectiveness of the developed algorithm.
Dalton, Lori Anne. "Analysis and Optimization of Classifier Error Estimator Performance within a Bayesian Modeling Framework". Thesis, 2012. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10873.
Pełny tekst źródłaNagaraja, Srinidhi. "Multi-Antenna Communication Receivers Using Metaheuristics and Machine Learning Algorithms". Thesis, 2013. http://etd.iisc.ernet.in/2005/3442.
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