Những quyển sách tương tự: ANALYSIS OF LIGHTNING STRIKE EFFECTS ON POWER MOSFETS AND PROTECTIVE CIRCUIT DESIGN /
- COMPARATIVE ANALYSIS OF LIGHTNING TRANSIENTS AND PROTECTION TECHNIQUES IN RURAL AND URBAN POWER TRANSMISSION SYSTEMS USING MATLAB/ SIMULINK /
- PHYSICS BASED MODELING AND CIRCUIT LEVEL EVALUATION OF SI-ON SIC MOSFET FOR HIGH-SPEED AND LOW POWER VLSI APPLICATIONS /
- DESIGN AND PERFORMANCE ANALYSIS OF LOW POWER LOW NOISE DUAL GATED GRAPHENE-MOSFET BASED VCO FOR WIRELESS APPLICATIONS /
- REAL AND REACTIVE POWER-BASED LOAD COMPARATIVE PERFORMANCE OF MOSFET, IGBT AND TRIAC ARCHITECTURES /
- SIMULATION AND CHARACTERIZATION OF SILICON ON INSULATOR (SOL) MOSFET /
- SIMULATION AND CHARACTERIZATION OF SILICON –ON- INSULATOR (SOL) MOSFET /
Đề tài: Electrical, Electronic and Communication Engineering.
- DESIGN AND ANALYSIS OF METAMATERIAL BASED BIOSENSOR TO DETERMINE BLOOD GLUCOSE CONCENTRATION /
- A COMPUTATIONALLY EFFICIENT DEEP LEARNING FRAMEWORK FOR SLEEP APNEA DETECTION /
- TEMPERATURE AND STATE OF CHARGE AWARE FAST CHARGING FOR LITHIUM-ION BATTERY SYSTEM /
- INTERPOLATION BASED ADAPTIVE REVERSIBLE DATA HIDING FOR DIGITAL IMAGE APPLICATIONS /
- ENERGY EFFICIENT OPERATIONS OF COMP BASED LTE-A CELLULAR NETWORKS WITH HYBERID POWER SUPPLIES /
- DESIGN AND CHARACTERIZATION OF BULK AND SOL FINFETS /
Đề tài: This Thesis Paper of EECE in BSc Program.
- A COMPUTATIONALLY EFFICIENT DEEP LEARNING FRAMEWORK FOR SLEEP APNEA DETECTION /
- TEMPERATURE AND STATE OF CHARGE AWARE FAST CHARGING FOR LITHIUM-ION BATTERY SYSTEM /
- A COMPARATIVE STUDY OF INORGANIC LEAD HALIDE PEROVSKITES BY ANALYZING THEIR ELECTRICAL, OPTICAL AND MECHANICAL PROPERTIES /
- A COMPREHENSIVE INVESTIGATION OF GaSb/GaAs0.5Sb0.5/GaAs BASED DG-HJ-SP-HD VERTICAL TUNNEL FET FOR OPTIMIZED LOW POWER APPLICATIONS: EXPLORING THE IMPACT OF DEVICE PARAMETER VARIATIONS /
- PERFORMANCE ANALYSIS OF CONTEMPORARY POWER DISTRIBUTION NETWORKS USING IEEE 13 BUS SYSTEM /
- AN IOT BASED HEALTHCARE SOLUTION AND MEDICAL SPECIALTY CLASSIFICATION FROM BANGLA TEXT USING MACHINE AND DEEP LEARNING MODELS /