Fundamentals of electrical engineering i

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1 Signals represent information

2 Structure of communication systems

3 The fundamental signal

4 Introduction problems

4.3 Advanced modems

Signals and systems

Complex numbers

1 Elemental signals

1.2 Complex exponentials

1.3 Real exponentials

1.6 Square wave

2 Signal decomposition

3 Discrete-time signals

4 Introduction to systems

5 Simple systems

5.4 Time reversal

5.5 Derivative systems and integrators

5.6 Linear systems

5.7 Time-invariant systems

6 Signals and systems problems

Analog signal processing

Voltage, current, and generic circuit elements

1 Ideal circuit elements

2 Ideal and real-world circuit elements

3 Electric circuits and interconnection laws

3.1 Kirchhoff's current law

3.2 Kirchhoff's voltage law (kvl)

4 Power dissipation in resistor circuits

5 Series and parallel circuits

6 Equivalent circuits: resistors and sources

7 Circuits with capacitors and inductors

8 The impedance concept

9 Time and frequency domains

10 Power in the frequency domain

11 Equivalent circuits: impedances and sources

12 Transfer functions

13 Designing transfer functions

14 Formal circuit methods: node method

15 Power conservation in circuits

17 Dependent sources

18 Operational amplifiers

20 Analog signal processing problems

20.1 Simple circuit analysis

20.2 Solving simple circuits

20.3 Equivalent resistance

20.4 Superposition principle

20.5 Current and voltage divider

20.6 Thévenin and mayer-norton equivalents

20.7 Detective work

20.8 Bridge circuits

20.9 Cartesian to polar conversion

20.10 The complex plane

20.11 Cool curves

20.12 Trigonometric identities and complex exponentials

20.13 Transfer functions

20.14 Using impedances

20.15 Measurement chaos

20.16 Transfer functions

20.17 A simple circuit

20.18 Circuit design

20.19 Equivalent circuits and power

20.20 Power transmission

20.21 Optimal power transmission

20.22 Big is beautiful

20.24 Circuit detective work

20.25 Mystery circuit

20.26 More circuit detective work

20.27 Linear, time-invariant systems

20.28 Long and sleepless nights

20.29 A testing circuit

20.30 Black-box circuit

20.31 Solving a mystery circuit

20.32 Find the load impedance

20.33 Analog “hum” rejection

20.34 An interesting circuit

20.35 A simple circuit

20.36 An interesting and useful circuit

20.37 A circuit problem

20.38 Analog computers

20.39 Transfer functions and circuits

20.40 Fun in the lab

20.41 Dependent sources

20.42 Operational amplifiers

20.43 Op-amp circuit

20.44 Why op-amps are useful

20.45 Operational amplifiers

20.46 Designing a bandpass filter

20.47 Pre-emphasis or de-emphasis?

20.48 Active filter

20.49 This is a filter?

20.50 Optical receivers

20.51 Reverse engineering

Frequency domain

Introduction to the frequency domain

1 Complex fourier series

2 Classic fourier series

3 A signal's spectrum

4 Fourier series approximation of signals

5 Encoding information in the frequency domain

6 Filtering periodic signals

7 Derivation of the fourier transform

8 Linear time invariant systems

9 Modeling the speech signal

10 Frequency domain problems

10.1 Simple fourier series

10.2 Fourier series

10.3 Phase distortion

10.4 Approximating periodic signals

10.5 Long, hot days

10.6 Fourier transform pairs

10.7 Duality in fourier transforms

10.8 Spectra of pulse sequences

10.9 Spectra of digital communication signals

10.10 Lowpass filtering a square wave

10.11 Mathematics with circuits

10.12 Where is that sound coming from?

10.13 Arrangements of systems

10.14 Filtering

10.15 Circuits filter!

10.16 Reverberation

10.17 Echoes in telephone systems

10.18 Effective drug delivery

10.19 Catching speeders with radar

10.20 Demodulating an am signal

10.21 Unusual amplitude modulation

10.22 Sammy falls asleep...

10.24 Am stereo

10.25 Novel am stereo method

10.26 A radical radio idea

10.27 Secret communication

10.28 Signal scrambling

Digital signal processing

Introduction to digital signal processing

1 Introduction to computer organization

2 The sampling theorem

3 Amplitude quantization

4 Discrete-time signals and systems

4.1 Real- and complex-valued signals

4.2 Complex exponentials

4.4 Unit sample

4.6 Symbolic signals

4.7 Discrete-time systems

5 Discrete-time fourier transform (dtft)

6 Discrete fourier transforms (dft)

7 Dft: computational complexity

8 Fast fourier transform (fft)

10 Discrete-time systems

11 Discrete-time systems in the time-domain

12 Discrete-time systems in the frequency domain

13 Filtering in the frequency domain

14 Efficiency of frequency-domain filtering

15 Discrete-time filtering of analog signals

16 Digital signal processing problems

16.1 Sampling and filtering

16.2 Non-standard sampling

16.3 A different sampling scheme

16.4 Bandpass sampling

16.5 Sampling signals

16.6 Hardware error

16.7 Simple d/a converter

16.8 Discrete-time fourier transforms

16.9 Spectra of finite-duration signals

16.10 Just whistlin'

16.11 Discrete-time filtering

16.12 A digital filter

16.13 A special discrete-time filter

16.14 Simulating the real world

16.15 Derivatives

16.17 Dsp tricks

16.18 Discrete cosine transform (dct)

16.19 A digital filter

16.20 Another digital filter

16.21 Yet another digital filter

16.22 A digital filter in the frequency domain

16.23 Digital filters

16.24 Digital filtering

16.25 Detective work

16.26 Time reversal has uses

16.27 Removing “hum”

16.28 Digital am receiver

16.30 Stock market data processing

16.32 Digital filtering of analog signals

16.33 Signal compression

Information communication

Information communication

1 Types of communication channels

2 Wireline channels

3 Wireless channels

4 Line-of-sight transmission

5 The ionosphere and communications

6 Communication with satellites

7 Noise and interference

8 Channel models

9 Baseband communication

10 Modulated communication

11 Signal-to-noise ratio of an amplitude-modulated signal

12 Digital communication

13 Binary phase shift keying

14 Frequency shift keying

15 Digital communication receivers

16 Digital communication in the presence of noise

17 Digital communication system properties

18 Digital channels

20 Source coding theorem

21 Compression and the huffman code

22 Subtlies of coding

23 Channel coding

24 Repetition codes

25 Block channel coding

26 Error-correcting codes: hamming distance

27 Error-correcting codes: channel decoding

28 Error-correcting codes: hamming codes

29 Noisy channel coding theorem

30 Capacity of a channel

31 Comparison of analog and digital communication

32 Communication networks

33 Message routing

34 Network architectures and interconnection

36 Communication protocols

37 Information communication problems

37.1 Signals on transmission lines

37.2 Noise in am systems

37.3 Complementary filters

37.4 Phase modulation

37.5 Digital amplitude modulation

37.6 Anti-jamming

37.7 Secret comunications

37.9 A novel communication system

37.10 Multi-tone digital communication

37.11 City radio channels

37.12 Downlink signal sets

37.13 Mixed analog and digital transmission

37.14 Digital stereo

37.15 Digital and analog speech communication

37.16 Source compression

37.17 Source compression

37.18 Speech compression

37.19 Digital communication

37.20 Signal compression

37.21 Universal product code

37.22 Error correcting codes

37.23 Digital communication

37.24 Overly designed error correction codes

37.25 Error correction?

37.26 Selective error correction

37.27 Compact disk

37.28 Communication system design

37.30 Digital cellular telephones

37.31 Optimal ethernet random access protocols

37.32 Repeaters

37.33 Designing a speech communication system

37.34 Digital vs. analog

1 Permutations and combinations

2 Frequency allocations

Source: OpenStax, Fundamentals of electrical engineering i. OpenStax CNX. Aug 06, 2008 Download for free at http://legacy.cnx.org/content/col10040/1.9

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