Arabic digits speech recognition and speaker identification in noisy environment using a hybrid model of VQ and GMM

This paper presents an automatic speaker identification and speech recognition for Arabic digits in noisy environment. In this work, the proposed system is able to identify the speaker after saving his voice in the database and adding noise. The mel frequency cepstral coefficients (MFCC) is the best approach used in building a program in the Matlab platform; also, the quantization is used for generating the codebooks. The Gaussian mixture modelling (GMM) algorithms are used to generate template, feature-matching purpose. In this paper, we have proposed a system based on MFCC-GMM and MFCC-VQ Approaches on the one hand and by using the Hybrid Approach MFCC-VQ-GMM on the other hand for speaker modeling. The White Gaussian noise is added to the clean speech at several signal-to-noise ratio (SNR) levels to test the system in a noisy environment. The proposed system gives good results in recognition rate

Foretaksorganisering av spesialisthelsetjenesten – mer profesjonell og autonom ledelse?

Master's thesis in Change managementDenne oppgavens intensjon har vært å studere helseforetakenes autonomi og ledelse i lyse av Stortingets styring av helseforetakene. Det er helseforetakenes autonomi opp mot Stortingets engasjement i sykehussaker både før og etter reformen som er undersøkt. Videre er ledelsesautonomi undersøkt ved se på om profesjonalisering av lederrollen kommer til uttrykk i helseforetakene, slik sykehusreformen (2002) legger opp til. I følge sykehusreformen skal de folkevalgte på Stortinget ha en tilbaketrukket rolle i styringen av helseforetakene. I den grad Stortinget vil engasjere seg, er det i mer overordnede prinsippspørsmål. Sykehusreformen trekker også frem ledelsesutfordringer i helsesektoren og foreslår økt oppmerksomhet på ledelsesutvikling og profesjonalisering av lederrollen. Oppgavens problemstilling ble utledet med en hovedantakelse om at Stortingets engasjement i sykehussaker er begrenset etter innføringen av reformen og en mer profesjonalisert ledelse i helseforetakene. Den alternative antakelsen er utledet med en forventning om økt engasjement i sykehussaker og begrenset ledelsesautonomi. De empiriske funnene viser at det er økt fokus på profesjonalisert ledelse i helseforetakene. Dette fordi at det ikke stilles krav til medisinsk bakgrunn i topplederstillingene, men snarere krav om ledelseskompetanse og erfaring. Flertallet av dagens toppledere har tilleggsutdannelser innenfor ledelse. Stortingets engasjement i sykehussaker har økt etter innføringen av reformen og det stilles flere detaljspørsmål. Odda-saken illustrerer Stortingets engasjement ytterligere. En nedleggelse av akuttkirurgien, slik helseforetkane ble instruert til og saken vedtatt i foretaksmøtet, havnet på Stortinget og helseministeren måtte snu i saken. For helseforetakenes ledelse betydde stortingets inngripen at de fikk redusert sin ledelsesautonomi. En økende profesjonalisering av ledelsesrollen i helseforetakene har ikke betydd økt ledelsesautonomi i alle saker. Foretaksledelsen opplever derfor at deres autonomi kan variere med saksområde slik blant annet Odda-saken viser, samt de mange detaljspørsmålene stortingsrepresentantene stiller om foretakenes virksomhet. Lederrollen i helseforetakene er profesjonalisert gjennom mer fokus på ledelsesutdanning mv., men det betyr ikke nødvendigvis mer ledelsesautonomi.submittedVersio

Blind Identification of Minimum Phase Channels Based On Higher Order Cumulants

This paper describes a blind algorithm, which is compared to the Zhang's and Safi's algorithms, for estimating of the minimum phase channel parameters. In order to identify blindly the impulse response of these channels, we have used Higher Order Statistics (HOS) to build our algorithm. The simulation results in noisy environment, demonstrate that the proposed method could estimate the phase and magnitude with high accuracy of these channels blindly and without any information about the input, except that the input excitation is identically and independent distribute (i.i.d) and non-Gaussian

Blind Identification of Minimum Phase Channels Based On Higher Order Cumulants

This paper describes a blind algorithm, which is compared to the Zhang's and Safi's algorithms, for estimating of the minimum phase channel parameters. In order to identify blindly the impulse response of these channels, we have used Higher Order Statistics (HOS) to build our algorithm. The simulation results in noisy environment, demonstrate that the proposed method could estimate the phase and magnitude with high accuracy of these channels blindly and without any information about the input, except that the input excitation is identically and independent distribute (i.i.d) and non-Gaussian

Blind Identification of Minimum Phase Channels Based On Higher Order Cumulants

This paper describes a blind algorithm, which is compared to the Zhang's and Safi's algorithms, for estimating of the minimum phase channel parameters. In order to identify blindly the impulse response of these channels, we have used Higher Order Statistics (HOS) to build our algorithm. The simulation results in noisy environment, demonstrate that the proposed method could estimate the phase and magnitude with high accuracy of these channels blindly and without any information about the input, except that the input excitation is identically and independent distribute (i.i.d) and non-Gaussian

Blind Identification Channel Using Higher Order Cumulants with Application to Equalization for MC-CDMA System

In this paper we propose an algorithm based on fourth order cumulants, for blind impulse response identification of frequency radio channels and downlink MC-CDMA system Equalization. In order to test its efficiency, we have compared with the Zhang et al algorithm, for that we considered on theoretical channel as the Proakis's 'B' channel and practical frequency selective fading channel, called Broadband Radio Access Network (BRAN C), normalized for MC-CDMA systems, excited by non-Gaussian sequences. In the part of MC-CDMA, we use the Minimum Mean Square Error (MMSE) equalizer after the channel identification to correct the channel's distortion. The simulation results, in noisy environment and for different signal to noise ratio (SNR), are presented to illustrate the performance of the proposed algorithm compared with the results obtained with the Zhang et al algorithm

Performance Evaluation of MC-CDMA Systems with Single User Detection Technique using Kernel and Linear Adaptive Method, Journal of Telecommunications and Information Technology, 2021, nr 4

Among all the techniques combining multi-carrier modulation and spread spectrum, the multi-carrier code division multiple access (MC-CDMA) system is by far the most widely studied. In this paper, we present the performance of the MC-CDMA system associated with key single-user detection techniques. We are interested in problems related to identification and equalization of mobile radio channels, using the kernel method in Hilbert space with a reproducing kernel, and a linear adaptive algorithm, for MC-CDMA systems. In this context, we tested the efficiency of these algorithms, considering practical frequency selective fading channels, called broadband radio access network (BRAN), standardized for MC-CDMA systems. As far as the equalization problem encountered after channel identification is concerned, we use the orthogonality restoration combination (ORC) and the minimum mean square error (MMSE) equalizer techniques to correct the distortion of the channel. Simulation results demonstrate that the kernel algorithm is efficient for practical channel

An Extended Version of the Proportional Adaptive Algorithm Based on Kernel Methods for Channel Identification with Binary Measurements, Journal of Telecommunications and Information Technology, 2022, nr 3

In recent years, kernel methods have provided an important alternative solution, as they offer a simple way of expanding linear algorithms to cover the non-linear mode as well. In this paper, we propose a novel recursive kernel approach allowing to identify the finite impulse response (FIR) in non-linear systems, with binary value output observations. This approach employs a kernel function to perform implicit data mapping. The transformation is performed by changing the basis of the data In a high-dimensional feature space in which the relations between the different variables become linearized. To assess the performance of the proposed approach, we have compared it with two other algorithms, such as proportionate normalized least-meansquare (PNLMS) and improved PNLMS (IPNLMS). For this purpose, we used three measurable frequency-selective fading radio channels, known as the broadband radio access Network (BRAN C, BRAN D, and BRAN E), which are standardized by the European Telecommunications Standards Institute (ETSI), and one theoretical frequency selective channel, known as the Macchi’s channel. Simulation results show that the proposed algorithm offers better results, even in high noise environments, and generates a lower mean square error (MSE) compared with PNLMS and IPNLMS