Registos relacionados: DESIGN OF A DUAL-BAND MICROSTRIP PATCH ANTENNA WITH ENHANCED BANDWIDTH AND GAIN FOR 5G APPLICATIONS /
- BANDWIDTH ENHANCEMENT AND PERFORMANCE ANALYSIS OF 6G V-BAND MICROSTRIP PATCH ANTENNA ESTIMATING ATMOSPHERIC AND PATH LOSS /
- INNOVATIVE DESIGN AND EVALUATION OF MICROSTRIP PATCH ANTENNAS FOR 5G COMMUNICATION IN MILLIMETER WAVE BAND /
- DESIGN AND PERFORMANCE ANALYSIS OF A MICROSTRIP PATCH ANTENNA FOR GNSS APPLICATIONS /
- DESIGN AND OPTIMIZATION OF MICROSTRIP ARRAY ANTENNA USING BOTH-SIDED MICROWAVE INTEGRATED CIRCUIT FOR GAIN ENHANCEMENT /
- DESIGN AND PARAMETRIC ANALYSIS OF H-PLANE HORN & MICROSTRIP PATCH ANTENNA AT X-BAND FOR INTERFERENCE SUPPERESION /
- COMPREHENSIVE DESIGN AND REALIZATION OF DUAL-BAND, KU-BAND AND X-BAND REFLECTARRAY ANTENNAS USING COMPACT SPLIT-RING UNIT CELLS /
Assunto: 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 /
Assunto: 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 /