Leaning Objectives
- To be able to analyse a circuit using both manual and computer based methods.
- To be able to specify and design an appropriate analogue filter for a given application
Learning / teaching plan
| Week | Lecture | Pages | Contribution to Assessment |
|---|---|---|---|
| 1 | The s-plane and the Laplace domain The s-plane, the general complex exponential excitation function, two-port networks, positive reak functions, positive semi-definite functions, properties of RC networks, properties of LC networks. | 1 - 16 | |
| 2,3 | State variables and state space representation State-space, obtaining state variables and state equations from transfer function, resistors, inductors and capacitors, formulation of state equations by nodal and mesh analysis, energy functions, formulation of state equations using energy functions. | 55 - 77 | |
| 4 | Transformations, canonical forms - eigen values Eigen values and eigen vectors, diagonal matrices, the Jordan canonical form. | 78 - 93 | |
| 5 | Assignment 1 - Presentations - 22nd September 2004 | 10 % | |
| 6,7 | Solution of network equations Solution of linear state equations through Laplace transformation, solution of transient equations, networks with sparse matrices. | 94 - 130 | |
| 8,9 | Synthesis of analogue circuits Realisation of LC driving point functions, RC driving point functions, RL driving point functions, synthesis of RLC circuits. Insertion power function and reflection coefficient, Butterworth filters, Chebyschev filters, transformation to obtain high-pass characteristics, band-pass and band-stop filters. Active Filters Active filters using gyrators, active filters using NICs, the state variable filter, switched capacitor filters. |
131 - 157
158 - 163 |
|
| 10 | Assignment 2 - Presentations - 3rd November 2004 | 10% | |
| 11,12 | Modern trends in circuit analysis and design Automatic equation formulation - modified nodal analysis, modelling of non-linear circuits - diodes and transistors, Spice, Tellegan's theorem, sensitivity and robust design, automatic design and use of Artificial Intelligence. | 164 - 213 | |
| 13 | Reserve | ||
| 14 | Assignment 3 - Presentations - 24th November 2004 | 10% | |
| Final examination | 70% | ||
| Total | 100 % |