- 
	
    Description 0This 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.No items in this section
- 
	
    Digital Signal and Image Processing 41- 
				
                How to Pass DSIP Importance + Strategy 17 minLecture2.1
- 
				
                Introduction to Digital Signal Processing 10 minLecture2.2
- 
				
                Determine signal is periodic or aperiodic 12 minLecture2.3
- 
				
                Determine signal is linear or non-linear 06 minLecture2.4
- 
				
                Determine Signal is Time varient or Invarient 06 minLecture2.5
- 
				
                Determine Signal is Static or Dynamic 05 minLecture2.6
- 
				
                Determine Signal is Causal or Non Causal 03 minLecture2.7
- 
				
                Determine Signal is Stable and unstable 05 minLecture2.8
- 
				
                Find Linear Convolution Part #1 14 minLecture2.9
- 
				
                Find Linear Convolution Part #2 16 minLecture2.10
- 
				
                Circular Convolution 09 minLecture2.11
- 
				
                Cross Correlation and Auto Correlation 16 minLecture2.12
- 
				
                Energy and Power Signal 22 minLecture2.13
- 
				
                Types of Signals 09 minLecture2.14
- 
				
                Stability Sum (find the range of linear time invariant signal for which impulse response is stable) 16 minLecture2.15
- 
				
                Output response (0.3 delta wala sum ) 05 minLecture2.16
- 
				
                Introduction to DFT 13 minLecture2.17
- 
				
                DFT(Discrete fourier transform) properties 12 minLecture2.18
- 
				
                Sum based on DFT properties 04 minLecture2.19
- 
				
                DFT Matrix Method 06 minLecture2.20
- 
				
                8 point matrix method 10 minLecture2.21
- 
				
                DIT-FFT(Decimation in time fast fourier transform) 16 minLecture2.22
- 
				
                Doubt solving ( 1 video me saare doubt clear ) 30 minLecture2.23
- 
				
                Introduction to Image Processing 10 minLecture2.24
- 
				
                Image File Format 10 minLecture2.25
- 
				
                Bitmap Image File Format 11 minLecture2.26
- 
				
                JPEG Image File Format 07 minLecture2.27
- 
				
                Tagged Image File Format (TIFF) 06 minLecture2.28
- 
				
                Gray Level Transformation 17 minLecture2.29
- 
				
                Zero memory Point Operation 18 minLecture2.30
- 
				
                Histogram Equalization 06 minLecture2.31
- 
				
                Region Growing in Image Segmentation 09 minLecture2.32
- 
				
                Region Splitting in Image Segmentation 05 minLecture2.33
- 
				
                Region Merging in Image Segmentation 11 minLecture2.34
- 
				
                Convolution , Mask and Filtering 17 minLecture2.35
- 
				
                Edge Detection 08 minLecture2.36
- 
				
                Prewitt and Sobel Mask 08 minLecture2.37
- 
				
                Robinson and Kirsch Mask 05 minLecture2.38
- 
				
                Laplacian Filter 07 minLecture2.39
- 
				
                Connectivity ( 4 , 8 and M connectivity ) 15 minLecture2.40
- 
				
                Discontinuities in Image Segmentation 09 minLecture2.41
 
- 
				
                
- 
	
    Artificial Intelligence and Soft Computing 39- 
				
                How to Pass AISC 18 minLecture3.1
- 
				
                Agent and Peas Description 07 minLecture3.2
- 
				
                Types of Agent 08 minLecture3.3
- 
				
                Learning Agent 08 minLecture3.4
- 
				
                Learning and Types of Learning 06 minLecture3.5
- 
				
                Soft computing vs Hard computing and Supervised learning vs Unsupervised Learning 10 minLecture3.6
- 
				
                BFS ( Breadth First Search ) Algorithm with solved Example 05 minLecture3.7
- 
				
                DFS ( Depth First Search ) Algorithm with solved Example 03 minLecture3.8
- 
				
                IDFS ( Iterative Depth First Search ) Algorithm with solved Example 03 minLecture3.9
- 
				
                GBFS Solved Example 07 minLecture3.10
- 
				
                A Star solved Example 13 minLecture3.11
- 
				
                Hill Climbing 04 minLecture3.12
- 
				
                Min Max Solved Example 06 minLecture3.13
- 
				
                Alpha-Beta Pruning Solved Example 13 minLecture3.14
- 
				
                Genetic Algorithm 05 minLecture3.15
- 
				
                Genetic Algorithm Max one Problem Solved Example 08 minLecture3.16
- 
				
                Propositional Logic (PL) Introduction 07 minLecture3.17
- 
				
                PL to CNF conversion With Solved Example 09 minLecture3.18
- 
				
                First-Order Logic (FOL) Solved Example 05 minLecture3.19
- 
				
                Resolution Tree Sum Part #1 08 minLecture3.20
- 
				
                Resolution Tree Sum Part #2 14 minLecture3.21
- 
				
                Partial Order Planning with Example 11 minLecture3.22
- 
				
                Introduction to Fuzzy Logic 04 minLecture3.23
- 
				
                Fuzzification and De-Fuzzification 06 minLecture3.24
- 
				
                Properties and Operation of Crisp and Fuzzy Sets 05 minLecture3.25
- 
				
                Crisp and Fuzzy Sets and Relations 11 minLecture3.26
- 
				
                Fuzzy Membership Function 08 minLecture3.27
- 
				
                Mamdani Fuzzy Model (Fuzzy Controller) with Solved Example 33 minLecture3.28
- 
				
                Introduction to ANN and structure of ANN 06 minLecture3.29
- 
				
                Mc-Culloch-Pitts Neural Model 03 minLecture3.30
- 
				
                Neural Network Architecture 05 minLecture3.31
- 
				
                Perceptron Learning (with solved example) 11 minLecture3.32
- 
				
                Activation functions in ANN (Discrete and Continuous) 04 minLecture3.33
- 
				
                Backpropagation Network (with solved example) 19 minLecture3.34
- 
				
                Self Organizing Maps and KSOMs 10 minLecture3.35
- 
				
                Introduction to Hybrid System 04 minLecture3.36
- 
				
                Neuro-Fuzzy System (Co-Operative and General NFS) 08 minLecture3.37
- 
				
                Fuzzy Inference System 07 minLecture3.38
- 
				
                Expert System 10 minLecture3.39
 
- 
				
                
- 
	
    Mobile Communication and Computing 36- 
				
                Introduction to Mobile Computing 06 minLecture4.1
- 
				
                GPRS Architecture 09 minLecture4.2
- 
				
                GSM architecture 20 minLecture4.3
- 
				
                Multiplexing 08 minLecture4.4
- 
				
                GEO MEO LEO Types of satellite Orbit 03 minLecture4.5
- 
				
                Handover and Types of Handover 06 minLecture4.6
- 
				
                Privacy and Authentication in GSM 08 minLecture4.7
- 
				
                Types of Handoffs and Handover 06 minLecture4.8
- 
				
                Mobile IP and Packet through tunnel working 05 minLecture4.9
- 
				
                3G UMTS architecture 05 minLecture4.10
- 
				
                Wireless local loop 06 minLecture4.11
- 
				
                PSTN Architecture 05 minLecture4.12
- 
				
                Cellular IP Standard 06 minLecture4.13
- 
				
                Bluetooth architecture 06 minLecture4.14
- 
				
                Android architecture 16 minLecture4.15
- 
				
                4G architecture 18 minLecture4.16
- 
				
                Frequency reuse concept in cellular system 09 minLecture4.17
- 
				
                Macro Mobility- MIPv6 and FMIPv6 08 minLecture4.18
- 
				
                Micro Mobility- HAWAII Architecture 07 minLecture4.19
- 
				
                Micro Mobility- HMIPv6 Hierarchical MIPv6 06 minLecture4.20
- 
				
                IP Address vs MAC Address 09 minLecture4.21
- 
				
                IPv4 Header Format 13 minLecture4.22
- 
				
                IPv6 11 minLecture4.23
- 
				
                IPv4 vs IPv6 10 minLecture4.24
- 
				
                SAE/LTE Architecture Part #1 12 minLecture4.25
- 
				
                SAE/LTE Architecture Part #2 07 minLecture4.26
- 
				
                VoLTE 09 minLecture4.27
- 
				
                Self-Organizing Networks (SON) Framework 08 minLecture4.28
- 
				
                IEEE 802.11 Architecture 09 minLecture4.29
- 
				
                IEEE 802.11 Protocol Architecture 11 minLecture4.30
- 
				
                Wifi Security – Wired Equivalent Privacy (WEP) 09 minLecture4.31
- 
				
                Wireless LAN Threats and Security 09 minLecture4.32
- 
				
                WiFi Protected Access 06 minLecture4.33
- 
				
                5G Introduction 08 minLecture4.34
- 
				
                HiperLAN Type 1 08 minLecture4.35
- 
				
                MCC Importance 13 minLecture4.36
 
- 
				
                
- 
	
    Notes of All Subjects 5- 
				
                Artificial Intelligence and Soft Computing Complete Notes ( Toppers Solution )Lecture5.1
- 
				
                Mobile Communication and Computing Notes ( Toppers Solution )Lecture5.2
- 
				
                Digital Signal Processing Handmade NotesLecture5.3
- 
				
                DSP University Paper SolutionLecture5.4
- 
				
                Digital Signal and Image Processing NotesLecture5.5
 
- 
				
                
    This content is protected, please login and enroll course to view this content!
        