Sökning: "modeling selection"
Visar resultat 1 - 5 av 201 avhandlingar innehållade orden modeling selection.
1. Model Selection and Sparse Modeling
Sammanfattning : Parametric signal models are used in a multitude of signal processing applications. This thesis deals with signals for which there are many candidate models, and it is not a priori known which model is the most appropriate one. LÄS MER
2. Configuration Design of a High Performance and Responsive Manufacturing System : Modeling and Evaluation
Sammanfattning : Configuring and reconfiguring a manufacturing system is presented as an issue with increasing importance due to higher frequency of system configuration or major reconfigurations to accommodate new set of requirements and/or the need to configure the system to make it usable across generations of products or product families. This research has focused in the modeling, evaluation and selection decisions which involves multiple, incommensurate and conflicting objectives. LÄS MER
3. Universal Instruction Selection
Sammanfattning : In code generation, instruction selection chooses instructions to implement a given program under compilation, global code motion moves computations from one part of the program to another, and block ordering places program blocks in a consecutive sequence. Local instruction selection chooses instructions one program block at a time while global instruction selection does so for the entire function. LÄS MER
4. Modeling Genome Evolution : Creation, Change and Destruction
Sammanfattning : Historically, evolution has been studied either by looking at morphological traits in living organisms and the fossil record, or by using bioinformatics and comparative genomics. While highly useful for deducing evolutionary history, these approaches are not particularly well suited for studying the mechanisms of evolution. LÄS MER
5. Covariate Model Building in Nonlinear Mixed Effects Models
Sammanfattning : Population pharmacokinetic-pharmacodynamic (PK-PD) models can be fitted using nonlinear mixed effects modelling (NONMEM). This is an efficient way of learning about drugs and diseases from data collected in clinical trials. LÄS MER