prediction of gain in ld-celp using hybrid genetic/pso-neural models
نویسندگان
چکیده
in this paper, the gain in ld-celp speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (pso) algorithms to optimize the structure and parameters of neural networks. elman, multi-layer perceptron (mlp) and fuzzy artmap are the candidate neural models. the optimized number of nodes in the first and second hidden layers of elman and mlp and also the initial weights and biases of these nets are determined by genetic algorithm (ga) and pso. in the fuzzy artmap, the choice parameter, , learning rate, , and vigilance parameter, , are selected by ga and pso, as well. in this way, the performance of ga and pso are compared when using different neural architectures in this application. empirical results show that when gain is predicted by elman and mlp neural networks with ga/psooptimized parameters, the segmental signal to noise ratio (snrseg) and mean opinion score (mos) are improved as compared to traditional implementation based on itu-t g.728 recommendation. on the other hand, fuzzy artmap-based gain predictor reduces the computational complexity noticeably, with no significant degradations in snrseg and mos.
منابع مشابه
Prediction of Gain in LD-CELP Using Hybrid Genetic/PSO-Neural Models
In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...
متن کاملPrediction of Gain in LD-CELP Using Hybrid Genetic/PSO-Neural Models
In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...
متن کاملPrediction of Gain in LD-CELP Using Hybrid Genetic/PSO-Neural Models
Abstract: In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden la...
متن کاملComplexity Reduction of LD-CELP Speech Coding in Prediction of Gain Using Neural Networks
Reducing the computational complexity is desired in speech coding algorithms. In this paper, three neural gain predictors are proposed which can function as backward gain adaptation module of low delay-code excited linear prediction (LD-CELP) G.728 encoder, recommended by International Telecommunication Union-Telecom sector (ITU-T, formerly CCITT). Elman, multilayer perceptron (MLP) and fuzzy A...
متن کاملEstimation of Reference Evapotranspiration Using Artificial Neural Network Models and the Hybrid Wavelet Neural Network
Estimation of evapotranspiration is essential for planning, designing and managing irrigation and drainage schemes, as well as water resources management. In this research, artificial neural networks, neural network wavelet model, multivariate regression and Hargreaves' empirical method were used to estimate reference evapotranspiration in order to determine the best model in terms of efficienc...
متن کاملAvailability Prediction of the Repairable Equipment using Artificial Neural Network and Time Series Models
In this paper, one of the most important criterion in public services quality named availability is evaluated by using artificial neural network (ANN). In addition, the availability values are predicted for future periods by using exponential weighted moving average (EWMA) scheme and some time series models (TSM) including autoregressive (AR), moving average (MA) and autoregressive moving avera...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
journal of advances in computer researchجلد ۲، شماره ۱، صفحات ۱-۱۲
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023