Revitalize Numenta HTM - Hierarchical Temporal Memory

Numenta HTM (Hierarchical Temporal Memory) is a biologically constrained machine intelligence technology that models the structural and algorithmic properties of the mammalian neocortex

https://github.com/berlinbrown/htm.java

This is adding updates to the project.


The visualizer simulates a room thermostat reporting 24 hourly readings each day:

```text

12 AM 64°F → 1 AM 63°F → ... → Noon 76°F → ... → 11 PM 65°F → next day

```

This example runs the complete learning path:

```text

hour ─────────→ periodic ScalarEncoder ─┐

                                       ├→ Spatial Pooler → active columns → Temporal Memory

temperature ──→ ScalarEncoder ─────────┘

```

The temperatures are simulated sensor readings, but they are ordinary real-world

values processed by the actual encoder and Spatial Pooler. Numbers such as

`[2, 3, 5]` are internal column addresses, not temperatures and not numbers the

model is learning to count.

Also converted some of NAB - https://github.com/numenta/NAB/


Let's go AGI!




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