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EE40: Introduction to Microelectronic Circuits

EE40: Introduction to Microelectronic Circuits. Summer 2004 Alessandro Pinto apinto@eecs.berkeley.edu. Staff. TAs Wei Mao maowei@eecs.berkeley.edu Renaldi Winoto winoto@eecs.berkeley.edu Reader Haryanto Kurniawan haryanto@uclink.berkeley.edu. Course Material. Main reference

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EE40: Introduction to Microelectronic Circuits

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  1. EE40: Introduction to Microelectronic Circuits Summer 2004 Alessandro Pinto apinto@eecs.berkeley.edu

  2. Staff • TAs • Wei Maomaowei@eecs.berkeley.edu • Renaldi Winotowinoto@eecs.berkeley.edu • Reader • Haryanto Kurniawanharyanto@uclink.berkeley.edu Alessandro Pinto, EE40 Summer 2004

  3. Course Material • Main reference • http://www-inst.eecs.berkeley.edu/~ee40 • Textbook (s) • Electrical Engineering Principles and Applications by Allan R. Hambley. • Reader available at Copy Central, 2483 Hearst Avenue • Publications • Selected pubs posted on the web Alessandro Pinto, EE40 Summer 2004

  4. Course Organization • Lectures: 3 x week (20 total) • Labs • Experimenting and verifying • Building a complete system: mixer, tone control, amplifier, power supply, control • Discussion sessions • More examples, exercise, exams preparation • Homework • Weekly, for a better understanding • Exams • 2 midterms, 1 final • Grade • HW: 10%, LAB: 10%, MID: 20%, FINAL: 40% Alessandro Pinto, EE40 Summer 2004

  5. Table of contents • Circuit components • Resistor, Dependent sources, Operational amplifier • Circuit Analysis • Node, Loop/Mesh, Equivalent circuits • First order circuit • Active devices • CMOS transistor • Digital Circuits • Logic gates, Boolean algebra • Gates design • Minimization • Extra Topics CAD for electronic circuits Alessandro Pinto, EE40 Summer 2004

  6. Prerequisites • Math 1B • Physics 7B Alessandro Pinto, EE40 Summer 2004

  7. Lecture 1 • Illustrates the historical background • Electricity • Transistor • Monolithic integration • Moore’s law • Introduces signals: Analog and Digital Alessandro Pinto, EE40 Summer 2004

  8. History of EE: Electricity Hans Christian Oersted’s Experiment (1820) Michael Faraday’s Experiment (1831) (Source: Molecular Expression) Maxwell’s Equations (1831) Alessandro Pinto, EE40 Summer 2004

  9. History of EE: Transistor Collector J. Bardeen,W. Brattain and W. Shockley, 1939-1947 Base Emitter BJT C MOSFET D B G E S Alessandro Pinto, EE40 Summer 2004

  10. History of EE: Integration Resistor Capacitor Inductor Diode Transistor Jack S. Kilby (1958) Monolithic (one piece) circuits: built form a silicon substrate Alessandro Pinto, EE40 Summer 2004

  11. Today’s Chips: Moore’s Law Gordon Moore, 1965 • Implications • Cost per device halves every 18 months • More transistors on the same area, more complex and powerful chips • Future chips are very hard to design!!! • Fabrication cost is becoming prohibitive Number of transistor per square inch doubles approximately every18 months Alessandro Pinto, EE40 Summer 2004

  12. Today’s Chips: An Example P4 2.4 Ghz, 1.5V, 131mm2 300mm wafer, 90nm 90nm transistor (Intel) Hair size (1024px) Alessandro Pinto, EE40 Summer 2004

  13. Signals: Analog vs. Digital g(t) f(t) t t Analog: Analogous to some physical quantity Digital: can be represented using a finite number of digits Alessandro Pinto, EE40 Summer 2004

  14. Example of Analog Signal • Properties: • Dynamic range: maxV – minV • Frequency: number of cycles in one second A (440Hz) piano key stroke Voltage (V) Time (s) Alessandro Pinto, EE40 Summer 2004

  15. Analog Circuits • It is an electronic subsystem which operates entirely on analog signals i(t) o(t) Amplifier o(t) = Ki(t) Alessandro Pinto, EE40 Summer 2004

  16. Digital Circuits • It is an electronic subsystem which operates entirely on numbers (using, for instance, binary representation) a sum 1-bit Adder b carry Alessandro Pinto, EE40 Summer 2004

  17. Encoding of Digital Signals +1.5 V 5 → 101 1 threshold +1.5 V noise margin 0 0 V 0 V +1.5 V • We use binary digits • Two values: {0 , 1} • Positional system • Encoded by two voltage levels • +1.5 V → 1 , 0 V → 0 Alessandro Pinto, EE40 Summer 2004

  18. Why Digital? • Digital signals are easy and cheap to store • Digital signals are insensible to noise • Boolean algebra can be used to represent, manipulate, minimize logic functions • Digital signal processing is easier and relatively less expensive than analog signal processing Alessandro Pinto, EE40 Summer 2004

  19. Digital Representation of Analog Signals • Problem: represent f(t) using a finite number of binary digits • Example: A key stroke using 6 bits • Only 64 possible values, hence not all values can be represented • Quantization error: due to finite number of digits • Time sampling: time is continuous but we want a finite sequence of numbers Alessandro Pinto, EE40 Summer 2004

  20. Digital Representation of Analog Signals Dynamic Range: [-30,30] V Precision: 5 V Sampling f(t) t t Quantization 1100 1011 0100 0101 0110 0001 0010 1001 1100 0100 0011 0010 0011 1011 1010 1001 1000 0111 Result 0110 0101 -5V 0100 -10V 0011 -15V 0010 -20V 0001 -25V 0000 -30V Alessandro Pinto, EE40 Summer 2004

  21. Digital Representation of Logic Functions • Boolean Algebra: • Variables can take values 0 or 1 (true or false) • Operators on variables: • a AND b a·b • a OR b a+b • NOT b b • Any logic expression can be built using these basic logic functions • Example: exclusive OR Alessandro Pinto, EE40 Summer 2004

  22. Full Adder Example a sum 1-bit Adder b carry Alessandro Pinto, EE40 Summer 2004

  23. Summary • Analog signals are representation of physical quantities • Digital signals are less sensible to noise than analog signals • Digital signals can represent analog signals with arbitrary precision (at the expense of digital circuit cost) • Boolean algebra is a powerful mathematical tool for manipulating digital circuits Alessandro Pinto, EE40 Summer 2004

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