Dariusz Bismor, "Adaptive Algorithms for Active Noise Control in an Acoustic Duct"

 

 

 

Przedmowa (5)
Contents (5)
Preface (9)
1. Introduction (11)
1.1. Active noise control (12)
1.2. Overview (13)
1.3. General assumptions (15)
1.4. Active noise control laboratory (16)
2. Acoustic System Identification (21)
2.1. The necessity of identification experiments (21)
2.2. The linearity tests (37)
2.3. Non-parametric identification (43)
2.4. Parametric identification (49)
2.5. Influence of electrical equipement temperature (54)
2.6. Conclusions (56)
3. Feedforward Control Using FIR Filtering (57)
3.1. Feedforward control (57)
3.2. Adaptive filters (59)
3.3. Least Mean Squares algorithm (62)
3.4. Recursive Least Squares algorithm (77)
4. Feedforward Control Using IIR Filtering (83)
4.1. Infinite Impulse Response filter (83)
4.2. Least Mean Squares algorithm (85)
4.3. Recursive Least Squares algorithm (88)
5. Feedforward Control Using Neural Network (93)
5.1. Neural networks and active noise control (93)
5.2. Error back-propagation learning algorithm (97)
5.3. Conjugate gradient learning algorithm (100)
5.4. Conclusions concerning feedforward control (102)
6. Feedback Control (103)
6.1. Feedback control (103)
6.2. Feedback active noise control (106)
6.3. Minimum variance control (108)
6.4. Internal Model Control (113)
6.5. PID Control (119)
6.6. Conclusions (122)
7. Hybrid Control (123)
7.1. Parallel structure (123)
7.2. Extended Minimum Variance Control (127)
7.3. Feedforward and feedback internal model control (130)
7.4. Conclusions (135)
8. Summary (137)
8.1. Contributions of this book (137)
8.2. Main results (138)
8.3. Acknowledgements (139)
References (141)
Index and Glossary (145)
Index (145)
Glossary of symbols and abbreviations (148)

 

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