Curriculum
- 5 Sections
- 121 Lessons
- 40 Weeks
Expand all sectionsCollapse all sections
- DescriptionThis Bundle Includes Three Subjects (Videos + Notes ):
DSIP (Digital Signal and Image Processing): Includes Sums and Theoretical Concept Both
AISC (Artificial Intelligence and Soft Computing): Includes Sums and Theoretical Concept Both
MCC (Mobile Communication and Computing): Includes Theoretical Concept
What we Provide : 1) Video Lectures in Hindi ( taking the complicated concept to very Basic Level )
2) Topper Solution Notes ( The Best Paper solution in the Market )
3) How to Pass strategy (The Best course in Mumbai university which provides and video lectures and notes all at one place according to your syllabus )
Course Validity: Current Semester if Exams get postponed your validity will Extend too so not to worry about it.0 - Digital Signal and Image Processing41
- 2.1How to Pass DSIP Importance + Strategy17 Minutes
- 2.2Introduction to Digital Signal Processing10 Minutes
- 2.3Determine signal is periodic or aperiodic12 Minutes
- 2.4Determine signal is linear or non-linear6 Minutes
- 2.5Determine Signal is Time varient or Invarient6 Minutes
- 2.6Determine Signal is Static or Dynamic5 Minutes
- 2.7Determine Signal is Causal or Non Causal3 Minutes
- 2.8Determine Signal is Stable and unstable5 Minutes
- 2.9Find Linear Convolution Part #114 Minutes
- 2.10Find Linear Convolution Part #216 Minutes
- 2.11Circular Convolution9 Minutes
- 2.12Cross Correlation and Auto Correlation16 Minutes
- 2.13Energy and Power Signal22 Minutes
- 2.14Types of Signals9 Minutes
- 2.15Stability Sum (find the range of linear time invariant signal for which impulse response is stable)16 Minutes
- 2.16Output response (0.3 delta wala sum )5 Minutes
- 2.17Introduction to DFT13 Minutes
- 2.18DFT(Discrete fourier transform) properties12 Minutes
- 2.19Sum based on DFT properties4 Minutes
- 2.20DFT Matrix Method6 Minutes
- 2.218 point matrix method10 Minutes
- 2.22DIT-FFT(Decimation in time fast fourier transform)16 Minutes
- 2.23Doubt solving ( 1 video me saare doubt clear )30 Minutes
- 2.24Introduction to Image Processing10 Minutes
- 2.25Image File Format10 Minutes
- 2.26Bitmap Image File Format11 Minutes
- 2.27JPEG Image File Format7 Minutes
- 2.28Tagged Image File Format (TIFF)6 Minutes
- 2.29Gray Level Transformation17 Minutes
- 2.30Zero memory Point Operation18 Minutes
- 2.31Histogram Equalization6 Minutes
- 2.32Region Growing in Image Segmentation9 Minutes
- 2.33Region Splitting in Image Segmentation5 Minutes
- 2.34Region Merging in Image Segmentation11 Minutes
- 2.35Convolution , Mask and Filtering17 Minutes
- 2.36Edge Detection8 Minutes
- 2.37Prewitt and Sobel Mask8 Minutes
- 2.38Robinson and Kirsch Mask5 Minutes
- 2.39Laplacian Filter7 Minutes
- 2.40Connectivity ( 4 , 8 and M connectivity )15 Minutes
- 2.41Discontinuities in Image Segmentation9 Minutes
- Artificial Intelligence and Soft Computing39
- 3.1How to Pass AISC18 Minutes
- 3.2Agent and Peas Description7 Minutes
- 3.3Types of Agent8 Minutes
- 3.4Learning Agent8 Minutes
- 3.5Learning and Types of Learning6 Minutes
- 3.6Soft computing vs Hard computing and Supervised learning vs Unsupervised Learning10 Minutes
- 3.7BFS ( Breadth First Search ) Algorithm with solved Example5 Minutes
- 3.8DFS ( Depth First Search ) Algorithm with solved Example3 Minutes
- 3.9IDFS ( Iterative Depth First Search ) Algorithm with solved Example3 Minutes
- 3.10GBFS Solved Example7 Minutes
- 3.11A Star solved Example13 Minutes
- 3.12Hill Climbing4 Minutes
- 3.13Min Max Solved Example6 Minutes
- 3.14Alpha-Beta Pruning Solved Example13 Minutes
- 3.15Genetic Algorithm5 Minutes
- 3.16Genetic Algorithm Max one Problem Solved Example8 Minutes
- 3.17Propositional Logic (PL) Introduction7 Minutes
- 3.18PL to CNF conversion With Solved Example9 Minutes
- 3.19First-Order Logic (FOL) Solved Example5 Minutes
- 3.20Resolution Tree Sum Part #18 Minutes
- 3.21Resolution Tree Sum Part #214 Minutes
- 3.22Partial Order Planning with Example11 Minutes
- 3.23Introduction to Fuzzy Logic4 Minutes
- 3.24Fuzzification and De-Fuzzification6 Minutes
- 3.25Properties and Operation of Crisp and Fuzzy Sets5 Minutes
- 3.26Crisp and Fuzzy Sets and Relations11 Minutes
- 3.27Fuzzy Membership Function8 Minutes
- 3.28Mamdani Fuzzy Model (Fuzzy Controller) with Solved Example33 Minutes
- 3.29Introduction to ANN and structure of ANN6 Minutes
- 3.30Mc-Culloch-Pitts Neural Model3 Minutes
- 3.31Neural Network Architecture5 Minutes
- 3.32Perceptron Learning (with solved example)11 Minutes
- 3.33Activation functions in ANN (Discrete and Continuous)4 Minutes
- 3.34Backpropagation Network (with solved example)19 Minutes
- 3.35Self Organizing Maps and KSOMs10 Minutes
- 3.36Introduction to Hybrid System4 Minutes
- 3.37Neuro-Fuzzy System (Co-Operative and General NFS)8 Minutes
- 3.38Fuzzy Inference System7 Minutes
- 3.39Expert System10 Minutes
- Mobile Communication and Computing36
- 4.1Introduction to Mobile Computing6 Minutes
- 4.2GPRS Architecture9 Minutes
- 4.3GSM architecture20 Minutes
- 4.4Multiplexing8 Minutes
- 4.5GEO MEO LEO Types of satellite Orbit3 Minutes
- 4.6Handover and Types of Handover6 Minutes
- 4.7Privacy and Authentication in GSM8 Minutes
- 4.8Types of Handoffs and Handover6 Minutes
- 4.9Mobile IP and Packet through tunnel working5 Minutes
- 4.103G UMTS architecture5 Minutes
- 4.11Wireless local loop6 Minutes
- 4.12PSTN Architecture5 Minutes
- 4.13Cellular IP Standard6 Minutes
- 4.14Bluetooth architecture6 Minutes
- 4.15Android architecture16 Minutes
- 4.164G architecture18 Minutes
- 4.17Frequency reuse concept in cellular system9 Minutes
- 4.18Macro Mobility- MIPv6 and FMIPv68 Minutes
- 4.19Micro Mobility- HAWAII Architecture7 Minutes
- 4.20Micro Mobility- HMIPv6 Hierarchical MIPv66 Minutes
- 4.21IP Address vs MAC Address9 Minutes
- 4.22IPv4 Header Format13 Minutes
- 4.23IPv611 Minutes
- 4.24IPv4 vs IPv610 Minutes
- 4.25SAE/LTE Architecture Part #112 Minutes
- 4.26SAE/LTE Architecture Part #27 Minutes
- 4.27VoLTE9 Minutes
- 4.28Self-Organizing Networks (SON) Framework8 Minutes
- 4.29IEEE 802.11 Architecture9 Minutes
- 4.30IEEE 802.11 Protocol Architecture11 Minutes
- 4.31Wifi Security – Wired Equivalent Privacy (WEP)9 Minutes
- 4.32Wireless LAN Threats and Security9 Minutes
- 4.33WiFi Protected Access6 Minutes
- 4.345G Introduction8 Minutes
- 4.35HiperLAN Type 18 Minutes
- 4.36MCC Importance13 Minutes
- Notes of All Subjects5
Find Linear Convolution Part #1
Find Linear Convolution Part #1
In this video we have explain the basic concept to solve the sum of Linear convolution.
Linear convolution is the basic operation to calculate the output for any linear time-invariant system given its input and its impulse response. The linear convolution result of two arbitrary M × N and P × Q image functions will generally be (M + P − 1) × (N + Q − 1), hence we would like the DFT G ˆ ˜ to have these dimensions. Therefore, the M × N function f and the P × Q function h must both be zero-padded to size (M + P − 1) × (N + Q − 1).
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