[PDF] Top 20 Multiclient Identification System Using Adaptive Probabilistic Model

... and identification of human faces in a more practical and real-time face recognition ...detection system is based on the cascade Adaboost method to improve the precision and robustness toward unstable ... See full document

... Nonlinear system identification has been an area of active research for ...nonlinear system depicted in Figure ...Hammerstein model finds application in modeling the involuntary contraction of ... See full document

... is using the neural network to predict the values of VSM and ...and adaptive neuro-fuzzy inference system (ANFIS) will be ...LPM using the probabilistic neural network ...30-bus ... See full document

... The adaptive parameter identification method for the system with Bouc-Wen hysteresis has been ...of adaptive ob- servers and solves the stability problem. Adaptive algo- rithms of ... See full document

... the model more precisely, the PSM was used to generate hidden state predictions for a collection of chemostat evolution experiments for ...the model achieves a prediction accuracy rate of 85% to 93% for the ... See full document

... All the following experiments were carried out on a subset of the FERET face database [8]. We used 1,000 individuals: 500 for training the system and 500 for testing the perfor- mance. We use two images (one ... See full document

... for identification of single nucleotide variation (SNV), both somatic and germline, indicating that computational methods as well as sequencing protocols have a major impact on the sen- sitivity and specificity of ... See full document

... microscopic model, a macroscopic model directly describes the overall collective behaviour of the sys- ...macroscopic probabilistic model are the Rate Equations, which have been suc- cessfully ... See full document

... purpose, identification systems with a nonlinear struc- ture are used where a neural network is among these solu- tions ...in adaptive prediction and control [14, ...the system, and state machines ... See full document

... are Adaptive GMMRF model, Maximal similarity based region merging, Probabilistic hypergraphs, Intelligent scissors, Adaptive weighted distances, Interactive graph cut method based on improved ... See full document

... degree using colour features (RGB) with an adaptive network based fuzzy inference ...degree using this ...a model of quality testing and identification of basmati rice was built which ... See full document

... a system with a periodic impact as the control suffers ...that system identification cannot be attempted using these results, as the gains do not have sufficient time between impacts to attain ... See full document

... for model selection, which tries to avoid or reduce any possible bias introduced by relying on any particular test data sets, is cross validation (Stone 1974, Stoica et ... See full document

... propagation model based on the RSS values and localizes the blind node using ...self-adaptive model-based Wi-Fi indoor localization method ” introduced in [33] used extended versions of two ... See full document

... the adaptive filters, the limitation of invariance is ...process. Adaptive digital filters can be classified into adaptive Finite Impulse Response (FIR) filter, or commonly known as an ... See full document

... forecasting model that best fits the data ...series model which can be used for simulating stationary river flow sequences with high skewness and the long-term correlation structure of an ARMA(1,1) models ... See full document

... drive using model reference adaptive system with PI controller as reference model will limit the performance at low speed of ...reference model free from pure integration and ... See full document

... In modeling a collection of documents for infor- mation access applications, the documents are of- ten represented as a “bag of words”, i.e., as term vectors composed of the terms and corresponding counts for each ... See full document

... In model checking temporal logic, abstraction and abstraction refinement techniques have been studied[7,9], and in real time systems, the construction of abstract model has also been ...in model ... See full document

... Using similarity metric, we find the interest similarity between users. Then a friend matching graph is created. It is a weighted graph G=(V,E,W)where users in the system are represented as vertices and ... See full document