fix(docs): correct warmup values in cycles/channels .md files

Cycles:
- ebsw: warmup 1 bar → Math.Max(hpLength, ssfLength) + 3 (default 43)
- homod: warmup 1 bar → maxPeriod * 2 (default 100)

Channels:
- apchannel: warmup 1 bar → ⌈3/alpha⌉ (default 15); params None → alpha; outputs Single → Multiple
- jbands: warmup 1 bar → ⌈20 + 80 × period^0.36⌉
- uchannel: warmup 1 bar → Math.Max(strPeriod, centerPeriod)"

lib/cycles/ebsw/ebsw.md

@@ -7,14 +7,14 @@
 | **Parameters**   | `hpLength` (default 40), `ssfLength` (default 10)                      |
 | **Outputs**      | Single series (Ebsw)                       |
 | **Output range** | Varies (see docs)                     |
-| **Warmup**       | 1 bar                          |
+| **Warmup**       | `Math.Max(hpLength, ssfLength) + 3` bars (default 43)                          |
 
 ### TL;DR
 
 - EBSW is a refined cycle oscillator that combines a high-pass filter (trend removal), a Super-Smoother filter (noise removal), and Automatic Gain Co...
 - Parameterized by `hplength` (default 40), `ssflength` (default 10).
 - Output range: Varies (see docs).
-- Requires 1 bar of warmup before first valid output (IsHot = true).
+- Requires `Math.Max(hpLength, ssfLength) + 3` bars (default 43) of warmup before first valid output (IsHot = true).
 - Validated against TA-Lib, Skender, and Tulip reference implementations where available.
 
 EBSW is a refined cycle oscillator that combines a high-pass filter (trend removal), a Super-Smoother filter (noise removal), and Automatic Gain Control to produce a normalized $[-1, +1]$ output representing the current position within the dominant market cycle. Developed by John Ehlers as an improvement over the original Hilbert Transform SineWave, it provides cleaner turning point detection without requiring complex phase extraction mathematics.

lib/cycles/homod/homod.md

@@ -7,14 +7,14 @@
 | **Parameters**   | `minPeriod` (default 6.0), `maxPeriod` (default 50.0)                      |
 | **Outputs**      | Single series (Homod)                       |
 | **Output range** | Varies (see docs)                     |
-| **Warmup**       | 1 bar                          |
+| **Warmup**       | `maxPeriod * 2` bars (default 100)                          |
 
 ### TL;DR
 
 - HOMOD estimates the dominant cycle period of a market using homodyne mixing, a technique from radio engineering where a signal is multiplied by a d...
 - Parameterized by `minperiod` (default 6.0), `maxperiod` (default 50.0).
 - Output range: Varies (see docs).
-- Requires 1 bar of warmup before first valid output (IsHot = true).
+- Requires `maxPeriod * 2` bars (default 100) of warmup before first valid output (IsHot = true).
 - Validated against TA-Lib, Skender, and Tulip reference implementations where available.
 
 HOMOD estimates the dominant cycle period of a market using homodyne mixing, a technique from radio engineering where a signal is multiplied by a delayed copy of itself to expose the angular phase change between samples. The output is a continuously varying period measurement (in bars) that tracks the market's instantaneous cycle length, enabling adaptive indicator tuning. Developed by John Ehlers, it offers better noise rejection and stability than the raw Hilbert Transform period estimator.