Digital Lecture Notes

Handwriting-style, searchable PDF versions of handwritten tablet notes, typeset in LaTeX. 204 notes in 18 courses; figures and graphs come from the original drawings. The notes are written in Turkish, titles are translated.

Semester 2 · Spring 2021–22

Mathematics II 2 notes

• Series, vectors and multivariable functions (pp. 1–20)70 p.
• Multivariable functions, multiple integrals (pp. 21–32)57 p.

Semester 3 · Fall 2022–23

Differential Equations 13 notes

• Weeks 1–3 – First-order differential equations4 p.
• Week 1 – Introduction to differential equations (theory)7 p.
• Weeks 4–6 – Physical problems, existence–uniqueness, Picard, Wronskian, constant-coefficient equations4 p.
• Week 9 – Euler equations, reduction of order, introduction to series solutions8 p.
• After the midterm – Cauchy–Euler, reduction of order, series solutions, Laplace, convolution theorem5 p.
• Recitation 1 (extra session) – Families of curves and separable equations7 p.
• Week 1 Recitation (session 2) – Separable and homogeneous equations7 p.
• Week 2 Recitation (session 3) – Linear, Bernoulli and Riccati equations5 p.
• Week 9 Recitation – Cauchy–Euler equation and reduction of order4 p.
• Week 10 Recitation – Reduction of order method (equations with a known solution)4 p.
• Week 12 Recitation – Convolution and the Laplace transform4 p.
• Week 13 Recitation – Systems of differential equations5 p.
• Week 14 Recitation – Repeated eigenvalues and systems5 p.

Electronic Devices 4 notes

• Weeks 11 and 12 – MOSFET12 p.
• Semiconductors and the diode (pp. 1–20)22 p.
• Diode circuits, BJT, introduction to MOSFET (pp. 21–40)39 p.
• MOSFET: channel, i–v characteristic, operating regions (pp. 41–46)8 p.

Numerical Analysis 9 notes

• Lecture 1 – Calculus review7 p.
• My midterm notes 1 – Basic theorems, root finding, interpolation, numerical differentiation and integration7 p.
• Lecture 2 – Single-variable functions and root-finding methods7 p.
• Lecture 3 – Root-finding methods (continued): Newton, secant and error analysis6 p.
• Lecture 7 – Numerical differentiation8 p.
• Week 8 – Numerical integration7 p.
• Lecture 9 – Numerical methods for differential equations: Euler and higher-order Taylor methods5 p.
• Lecture 11 – Iterative methods for systems of linear equations7 p.
• Week 11 – Iterative methods for systems of linear equations8 p.

Semester 4 · Spring 2022–23

Circuit Theory II 1 notes

• Final exam study – Laplace, s-domain analysis, Fourier series, frequency response and passive filters8 p.

Electronics I 9 notes

• BJT – Lecture 1 review3 p.
• Lecture of 24 May – BJT small-signal models and the common-emitter amplifier7 p.
• Small Signal Models (review) – BJT small-signal models and amplifiers6 p.
• Recitation: BJT and MOSFET circuit analysis15 p.
• MOSFET small signal – small-signal model and amplifier configurations6 p.
• Lecture of 31 May – Common-base and common-collector amplifiers, MOSFET basics7 p.
• BJT problem review – operating regions and DC analysis examples4 p.
• Final note – BJT and MOSFET summary, small-signal models4 p.
• Notes – BJT small-signal models and the common-emitter amplifier8 p.

Signals and Systems 18 notes

• Lecture 1 – Signals: energy, power and basic operations7 p.
• Lecture 2 – Unit impulse and unit step functions, system properties8 p.
• Lecture 3 – Linear time-invariant (LTI) systems8 p.
• Lecture 4 – Properties of LTI systems, unit step response7 p.
• Lecture 5 – Continuous-time Fourier series7 p.
• Lecture 6 – Properties of the continuous-time Fourier series7 p.
• Lecture 7 – Discrete-time Fourier series8 p.
• Lectures 8–10 – Continuous-time Fourier transform11 p.
• Lecture 8 – Continuous-time Fourier transform8 p.
• Lecture 11 – Discrete-time Fourier transform (DTFT)6 p.
• Lecture 11 – Problem solutions (convolution and difference equations with the DTFT)2 p.
• Lecture 12 – Laplace transform7 p.
• Week 12 – DTFT, Laplace transform and ROC11 p.
• Lecture 13 – z-transform11 p.
• Week 13 – Laplace transform, ROC, inverse Laplace9 p.
• Recitation – Transformations, system properties, convolution, Fourier series (pages 1–21)11 p.
• Recitation notes – Fourier series and Fourier transform (pages 22–41)6 p.
• Recitation – Stability and convolution problems3 p.

Probability and Randomness 2 notes

• Homework 2 solutions: joint density, covariance, conditional expectation3 p.
• Notes for the final – Lectures 7–1222 p.

Semester 5 · Fall 2023–24

Analog Communication Systems 22 notes

• Lecture 2 – Signals, power/energy, basic signals and systems11 p.
• Lecture 3 – Fourier series expansions and spectrum11 p.
• Lecture 4 – Fourier series, Fourier transform and its properties12 p.
• Lecture 5 – Signal transmission through linear systems; energy and power spectral density9 p.
• Lecture 6 – Distortionless transmission, filters and modulation9 p.
• Lecture 7 – DSB-SC-AM: modulation and demodulation10 p.
• Lecture 8 – Frequency mixer, DSB-SC, AM modulation: power and efficiency12 p.
• Lecture 9 – DSB-LC-AM modulators and demodulators7 p.
• Lecture 10 – Single sideband (SSB) and FDM8 p.
• Lecture 11 – Superheterodyne receiver, angle modulation, NBFM8 p.
• Lecture 12 – Angle modulation, Carson's rule, single-tone FM/PM11 p.
• Lecture 13 – Angle modulation (FM): generation, demodulation, noise9 p.
• Recitation 1: Systems, Fourier Series & Transform12 p.
• Recitation 2: LTI channel, AM and multiplexing10 p.
• Recitation 3: SSB-AM, Weaver modulator, SSB-FDM2 p.
• ELM 361 Recitation 3 – SSB and FM problems14 p.
• DSB-LC-AM problem solution (Z1)3 p.
• ELM362 Final (2007), Question 1 solution4 p.
• ELEC 361 Midterm Exam (Fall 2023) solutions6 p.
• ELEC 361 Bonus Quiz solution (Fall 2023)3 p.
• Angle modulation: FM generation and demodulation4 p.
• ELEC 361 Midterm Exam (Fall 2023) solution3 p.

Electromagnetic Field Theory 27 notes

• Lecture 1 – Sources and fundamental postulates1 p.
• Lecture 2 – Law of motion, mass–velocity relation, electric interaction4 p.
• Lecture 3 – Electrostatics: Coulomb's law and the electric field5 p.
• Lecture 4 – Electric field and potential: grad, div, curl6 p.
• Lecture 5 – Electrostatic potential and equipotential surfaces8 p.
• Lecture 6 – Electrostatic potential and work3 p.
• Lecture 7 – Electric dipole, complex numbers, Gauss's theorem4 p.
• Lecture 8 – Gauss–Ostrogradsky theorem, Gauss's law9 p.
• Lecture 9 – Charge distributions and the Dirac distribution7 p.
• Lecture 10 – Dirac delta function and charge distributions7 p.
• Lecture 11 – Force on a surface charge3 p.
• Lecture 12 – Delta function and charge density expressions8 p.
• Lecture 13 – Dielectric media6 p.
• Lecture 14 – The concept and method of images9 p.
• Lecture 15 – Lorentz force, magnetic induction, current density15 p.
• Vector analysis: grad, div, curl and coordinate systems6 p.
• Fields of a charged sphere, disk and parallel planes5 p.
• Recitation 3 – Laplace's equation and boundary value problems7 p.
• Recitation 4 – Potential and energy in charge systems5 p.
• Recitation 5 – Charge distributions: potential, force, Gauss5 p.
• Applications of Gauss's law: sphere and cylinder5 p.
• Recitation 7 (after the midterm) – Concentric spherical/cylindrical surfaces4 p.
• Recitation 8 – Conductors: potential, surface charge, capacitance6 p.
• Recitation 9 – Method of images (corner, dielectric interface)6 p.
• Final exam study: 2023 past exam6 p.
• Final study note (recitation and lecture notes)36 p.
• Final exam study notes39 p.

Electromechanical Energy Conversion 1 notes

• Final note – electromechanical conversion, DC and induction machines15 p.

Electronics II 13 notes

• Lecture 2 – Intrinsic gain, cascode amplifier and current mirror9 p.
• Lecture 3 – Current Mirrors, Widlar/Wilson, Cascode Amplifier9 p.
• Lecture 4 – Cascode and differential amplifiers9 p.
• Lecture 5 – Differential amplifier: small signal, CMRR, common-mode range11 p.
• Lecture 6 – BJT differential amplifier and differential pair problems8 p.
• Lecture 7 – BJT differential amplifier, CMRR and active-loaded differential amplifier13 p.
• Lecture 8 – Active-loaded differential amplifier and frequency response7 p.
• Lecture 9 – Frequency response: low/high frequency, Miller's theorem10 p.
• Lecture 10 – BJT amplifier: low- and high-frequency response8 p.
• Lecture 11 – Feedback: General Structure, Voltage and Current Amplifiers9 p.
• Lecture 12 – Series-Series, Shunt-Shunt Feedback and Worked Examples10 p.
• Lecture 13 – Feedback Amplifier Examples7 p.
• Final exam study: feedback and frequency response27 p.

Semester 6 · Spring 2023–24

Control Systems 18 notes

• Control Systems – Lecture 13 p.
• Lecture 2 – Modeling, Laplace Transform & Partial Fractions8 p.
• Lecture 3 – Block Diagram & Signal Flow Graph10 p.
• Lecture 4 – Modeling: electrical systems, transfer function, state space11 p.
• Lecture 5 – State Space and 2nd Order Systems16 p.
• Lecture 6 – Transient / Steady State Response (1st & 2nd order)10 p.
• Lecture 7 – 2nd/higher order systems, time-domain specs11 p.
• Lecture 8 – Stability, Routh Criterion, Control Actions15 p.
• Lecture 9 – Accuracy of Systems: Steady-State Error11 p.
• Lecture 10 – Root Locus7 p.
• Lecture 11 – Root Locus (continued)9 p.
• Lecture 12 – Positive feedback root locus, lead/lag compensators13 p.
• Final exam study – Solution 16 p.
• Root locus and compensator design problems5 p.
• Steady-state error and closed-loop transfer function2 p.
• Chapter 7 Examples: Steady-State Error Problems7 p.
• Final exam study solutions (Routh, error, root locus)8 p.
• Root loci (final exam study)15 p.

Digital Communications 14 notes

• Lecture 1 – Digital communication system, channels and advantages4 p.
• Lecture 2 – Probability theory, random variables and processes14 p.
• Lecture 3 – Basic signals, Fourier transform, sampling16 p.
• Lecture 4 – Sampling theorem and types of sampling14 p.
• Lecture 5 – Flat-top sampling, PAM/PWM/PPM, TDM and PCM13 p.
• Lecture 6 – PCM, quantization, line codes and delta modulation10 p.
• Lecture 7 – PCM system example9 p.
• Lecture 8 – Baseband communication, matched filter, correlator11 p.
• Lecture 9 – Error probability in binary signaling and the MAP criterion11 p.
• Lecture 10 – Matched filter, ISI and the first Nyquist criterion9 p.
• Lecture 11 – RC pulse, controlled ISI, digital carrier modulation (PSK/FSK)10 p.
• Lecture 12 – FSK, ASK, QAM and the vector-space representation of M-ary modulation10 p.
• Lecture 13 – M-PSK and MFSK error probability curves7 p.
• Week 5 (Spring 2024) – Sample-and-hold, PAM/PWM/PPM, TDM and PCM9 p.

Fundamentals of Digital Signal Processing 13 notes

• Lecture 1 – Fundamentals of digital signal processing6 p.
• Lecture 2 – Discrete-time systems, LTI, convolution, FIR/IIR10 p.
• Lecture 3 – Difference equations, FIR/IIR, DTFT and frequency response10 p.
• Lecture 4 – Frequency response, DTFT and the Z-transform13 p.
• Lecture 5 – Properties of the Z-transform6 p.
• Lecture 6 – Z-transform, difference equations and sampling9 p.
• Lecture 7 – Downsampling, upsampling and LTI frequency response12 p.
• Lecture 8 – Group delay and linear phase9 p.
• Lecture 9 – Filter structures15 p.
• Lecture 10 – FIR filter types and design, STFT7 p.
• Lecture 11 – Quiz solution, FIR/IIR filter design9 p.
• Lecture 12 – Quiz solution, IIR filter design (bilinear transform), Butterworth11 p.
• Lecture 13 – DTFT, DFT, circular convolution and FFT9 p.

Semester 7 · Fall 2024–25

Image Processing 11 notes

• Lecture 1 – Introduction, image representation and the PGM format4 p.
• Lecture 2 – Image enhancement: intensity transformations and spatial filters6 p.
• Lecture 3 – Unsharp masking, gradient, histogram processing7 p.
• Lecture 5 – Filtering in the Frequency Domain6 p.
• Lecture 6 – Filtering in the frequency domain (Gaussian, Laplacian, homomorphic)7 p.
• Lecture 7 – Examples and image segmentation (edges, gradient, thresholding)6 p.
• Lecture 8 – Image thresholding7 p.
• Lecture 9 – Hough transform and connected components10 p.
• Lecture 10 – Morphological Image Processing7 p.
• Lecture 11 – Morphological Image Processing (continued)6 p.
• Lecture 12 – Granulometry, geometric transformation, feature extraction8 p.

RF System Design for Communications 16 notes

• Lecture 1 – Introduction to RF and basic concepts13 p.
• Lecture 3 – LNA, mixer, oscillator, PA, modulation, S-parameters19 p.
• Lecture 4 – Smith Chart, Power and Linearity12 p.
• Lecture 5 – Desensitization, Intermodulation, IIP3, Noise11 p.
• Lecture 6 – Noise, Noise Figure, Cascaded Stages, Noise Floor16 p.
• Lecture 7 – Receiver Noise Floor, Sensitivity, DR and SFDR8 p.
• Lecture 8 – Modulation Concepts, PAPR, ACPR, EVM, MER7 p.
• Lecture 9 – RF Link, Antenna Gain, Path Loss, Link Margin6 p.
• Lecture 10 – Receiver architectures (heterodyne, image frequency)12 p.
• Lecture 11 – Dual conversion, zero-IF, sliding IF and dual-band receivers14 p.
• Lecture 12 – Direct-conversion receiver, its disadvantages, I/Q mismatch13 p.
• Lecture 13 (part 2) – Phase shifting, Hartley/Weaver, image rejection10 p.
• Lecture 13 – Phase shifting, Hartley/Weaver, image rejection10 p.
• Lecture 1 review – RF basics, noise, receiver, antenna, filter13 p.
• Midterm study – Nonlinearity, noise, dynamic range30 p.
• Midterm study – Nonlinearity and noise (summary)5 p.

Fundamentals of Machine Learning 11 notes

• Lecture 2 – Metrics, distance measures, classification criteria12 p.
• Lecture 3 – Supervised learning, regression, MLE, MMSE and MAP7 p.
• Lecture 4 – Parametric estimation, MLE, Gaussian Mixtures, EM8 p.
• Lecture 5 – Naive Bayes, kernel density and k-NN3 p.
• Lecture 6 – Decision trees, regression trees, ensemble learning5 p.
• Lecture 7 – Feature selection, PCA, SVD, LDA and clustering5 p.
• Lecture 8 – Perceptron, backpropagation, activation functions and PyTorch9 p.
• Lecture 9 – CNN, RNN/LSTM, encoding and TF-IDF6 p.
• Lecture 10 – NLP: Tokenization, TF-IDF, Word2Vec6 p.
• Lecture 11 – RNN, attention and reinforcement learning7 p.
• Final exam study notes27 p.