SyllabusVideosClass NotesReference Text Books

**UNIT-I ** **ELECTRON DYNAMICS AND CRO:**

Motion of charged particles in electric and magnetic fields. Simple problems involving electric and magnetic fields only. Electrostatic and magnetic focusing. Principles of CRT,deflection sensitivity (Electrostatic and magnetic deflection), Parallel Electric and Magnetic fields,Perpendicular Electric and Magnetic fields.

**UNIT- II JUNCTION DIODE CHARACTERISTICS :**

Review of semi conductor Physics – n and p –type semiconductors, Mass Action Law, Continuity Equation, Hall Effect, Fermi level in intrinsic and extrinsicsemiconductors, Open-circuited p-n junction, The p-n junction Energy band diagram of PN diode, PN diode as a rectifier (forward bias and reverse bias), The current components in p-n diode, Law of junction, Diode equation, Volt-ampere characteristics of p-n diode, Temperature dependence of VI characteristic, Transition and Diffusion capacitances, Step graded junction, Breakdown Mechanisms in Semi Conductor (Avalanche and Zener breakdown) Diodes, Zener diode characteristics, Characteristics of Tunnel Diode with the help of energy band diagrams, Varactar Diode, LED, LCD. And photo diode.

**UNIT- III RECTIFIERS, FILTERS AND REGULATORS :**

Half wave rectifier, ripple factor, full wave rectifier, Harmonic components in a rectifier circuit, Inductor filter, Capacitor filter, L- section filter, Π- section filter, Multiple L-section and Multiple Πsection filter, and comparison of various filter circuit in terms of ripple factors, Simple circuit of a regulator using zener diode, Series and Shunt voltage regulators.

**UNIT- IV TRANSISTOR and FET CHARACTERISTICS :**

Junction transistor, Transistor current components, Transistor as an amplifier, Transistor construction, Detailed study of currents in a transistor, Transistor alpha, Input and Output characteristics of transistor in Common Base, Common Emitter, and Common

collector configurations, Relation between Alpha and Beta, typical transistor junction voltage values, JFETcharacteristics (Qualitative and Quantitative discussion), Small signal model of JFET, MOSFETcharacterisitics (Enhancement and depletion mode), Symbols of MOSFET, Comparison of Transistors,Introduction to SCR and UJT.

**UNIT-V BIASING AND STABILISATION :**

BJT biasing, DC equivalent model, criteria for fixing operating point, Fixedbias, Collector to base bias, Self bias techniques for stabilization, Stabilization factors, (S, S’, S'’),Compensation techniques, (Compensation against variation in VBE, Ico ,) Thermal run away, Thermal stability.

**UNIT- VI AMPLIFIERS :**

Small signal low frequency transistor amplifier circuits: h-parameter representation of a transistor, Analysis of single stage transistor amplifier using h-parameters: voltage gain, current gain, Input impedance and Output impedance. Comparison of transistor configurations in terms of AI, Ri ,Av, Ro.

**UNIT- VII FEEDBACK AMPLIFIERS :**

Concept of feedback, Classification of feedback amplifiers, Generalcharacteristics of negative feedback amplifiers, Effect of Feedback on input and output characteristics,Voltage series, voltage shunt, current series, and current shunt feedback amplifiers with discrete components and their analysis.

**UNIT-VIII OSCILLATORS :**

Condition for oscillations. RC-phase shift oscillators with Transistor and FET, Hartley andColpitts oscillators, Wein bridge oscillator, Crystal oscillators, Frequency and amplitude stability of oscillators.

Speech recognition technology is used more and more for telephone applications like travel booking and information, financial account information, customer service call routing, and directory assistance. Using constrained grammar recognition, such applications can achieve remarkably high accuracy. Research and development in speech recognition technology has continued to grow as the cost for implementing such voice-activated systems has dropped and the usefulness and efficacy of these systems has improved. For example, recognition systems optimized for telephone applications can often supply information about the confidence of a particular recognition, and if the confidence is low, it can trigger the application to prompt callers to confirm or repeat their request. Furthermore, speech recognition has enabled the automation of certain applications that are not automatable using push-button interactive voice response (IVR) systems, like directory assistance and systems that allow callers to "dial" by speaking names listed in an electronic phone book.

Speaker identity is correlated with the physiological and behavioral characteristics of the speaker. These characteristics exist both in the spectral envelope (vocal tract characteristics) and in the supra-segmental features (voice source characteristics and dynamic features spanning several segments). The most common short-term spectral measurements currently used are Linear Predictive Coding (LPC)-derived cepstral coefficients and their regression coefficients. A spectral envelope reconstructed from a truncated set of cepstral coefficients is much smoother than one reconstructed from LPC coefficients.

Therefore it provides a stabler representation from one repetition to another of a particular speaker's utterances. As for the regression coefficients, typically the first- and second-order coefficients are extracted at every frame period to represent the spectral dynamics. These coefficients are derivatives of the time functions of the cepstral coefficients and are respectively called the delta- and delta-delta-cepstral coefficients.

Speech recognition technology is used more and more for telephone applications like travel booking and information, financial account information, customer service call routing, and directory assistance. Using constrained grammar recognition, such applications can achieve remarkably high accuracy. Research and development in speech recognition technology has continued to grow as the cost for implementing such voice-activated systems has dropped and the usefulness and efficacy of these systems has improved. For example, recognition systems optimized for telephone applications can often supply information about the confidence of a particular recognition, and if the confidence is low, it can trigger the application to prompt callers to confirm or repeat their request. Furthermore, speech recognition has enabled the automation of certain applications that are not automatable using push-button interactive voice response (IVR) systems, like directory assistance and systems that allow callers to "dial" by speaking names listed in an electronic phone book.

Speaker identity is correlated with the physiological and behavioral characteristics of the speaker. These characteristics exist both in the spectral envelope (vocal tract characteristics) and in the supra-segmental features (voice source characteristics and dynamic features spanning several segments). The most common short-term spectral measurements currently used are Linear Predictive Coding (LPC)-derived cepstral coefficients and their regression coefficients. A spectral envelope reconstructed from a truncated set of cepstral coefficients is much smoother than one reconstructed from LPC coefficients.

Therefore it provides a stabler representation from one repetition to another of a particular speaker's utterances. As for the regression coefficients, typically the first- and second-order coefficients are extracted at every frame period to represent the spectral dynamics. These coefficients are derivatives of the time functions of the cepstral coefficients and are respectively called the delta- and delta-delta-cepstral coefficients.

**TEXT BOOKS :**

1. Electronic Devices and Circuits – J.Millman, C.C.Halkias, and Satyabratha Jit Tata McGraw Hill, 2nd Ed.,2007.

2. Electronic Devices and Circuits – R.L. Boylestad and Louis Nashelsky, Pearson/Prentice Hall,9thEdition,2006

**REFERENCES :**

1. Electronic Devices and Circuits – T.F. Bogart Jr., J.S.Beasley and G.Rico, Pearson Education, 6thedition, 2004.

2. Principles of Electronic Circuits – S.G.Burns and P.R.Bond, Galgotia Publications, 2nd Edn.., 1998.

3. Microelectronics – Millman and Grabel, Tata McGraw Hill, 1988.

4. Electronic Devices and Circuits – Dr. K. Lal Kishore, B.S. Publications, 2nd Edition, 2005.

5. Electronic Devices and Circuits- Prof GS N Raju I K International Publishing House Pvt .Ltd 2006

Translate »