## Lec 42 | Principles of Communication Systems-I |Lloyd- Max Quantization Algorithm| IIT KANPUR

Hello welcome to another module in this massive open online course so in this module so we are looking at quantization alright let us continue our discussion on quantization and this module we already looked at uniform quantization In this module let us look at the different algorithm for the design of a quantizer which

## Graph Theory: Repeated Nearest Neighbor Algorithm (RNNA)

– WELCOME TO A LESSON ON THE REPEATED NEAREST NEIGHBOR ALGORITHM. USING THE GRAPH HERE ON THE LEFT IN A PREVIOUS LESSON, WE FOUND THE LOWEST COST HAMILTONIAN CIRCUIT USING THE BRUTE FORCE ALGORITHM TO BE THE CIRCUIT “A,” B, C, E, D, “A” TO HAVE A TOTAL WEIGHT OF 19. WE KNEW THIS WAS

## Graph Theory: Kruskal’s Algorithm

– WELCOME TO A LESSON ON KRUSKAL’S ALGORITHM THAT’S USED TO FIND THE MINIMUM COSTS OF SPANNING TREE. FOR REVIEW, A SPANNING TREE IS A CONNECTED GRAPH USING ALL VERTICES IN WHICH THERE ARE NO CIRCUITS. IN OTHER WORDS, THERE’S A PATH FROM ANY VERTEX TO ANY OTHER VERTEX, BUT NO CIRCUITS. THE DARK BLUE

## Graph Theory: Sorted Edges Algorithm (Cheapest Link Algorithm)

– WELCOME TO A LESSON ON THE SORTED EDGES ALGORITHM THAT CAN BE USED TO TRY TO FIND THE OPTIMAL OR LOWEST COST HAMILTONIAN CIRCUIT. SO AS AN ALTERNATIVE OUR NEXT APPROACH WE’LL STEP BACK AND LOOK AT THE BIG PICTURE. WE DETERMINE A HAMILTONIAN CIRCUIT BY SELECTING EDGES WITH THE LEAST WEIGHT AND THEN

## Graph Theory: Nearest Neighbor Algorithm (NNA)

– WELCOME TO A LESSON ON THE NEAREST NEIGHBOR ALGORITHM THAT CAN BE USED WHEN ATTEMPTING TO FIND THE OPTIMAL HAMILTONIAN CIRCUIT. UNFORTUNATELY NO ONE HAS FOUND AN EFFICIENT AND OPTIMAL ALGORITHM TO SOLVE THE TRAVELING SALESPERSON PROBLEM. IT SEEMS UNLIKELY ANYONE EVER WILL. IF YOU WERE ABLE TO SOLVE THE TSP PROBLEM, YOU WOULD