Warrior_EA/Signals/README.md

# Signals Subsystem (Signals/)

## Overview
The Signals/ directory contains all trade signal generation logic for the Warrior EA. It includes both traditional indicator-based signals and advanced AI/ML-driven signals. Each signal is encapsulated in its own class, supporting modularity and extensibility.

## Key Components

### Signals.mqh
- Main orchestration file for signal modules.
- Includes both traditional and AI/ML signal classes.
- Facilitates integration of filters (news, session, etc.) and advanced signals.

### AI/ML-Driven Signals
- **SignalLSTM.mqh**: Implements an LSTM-based neural network signal generator. Integrates with the AI subsystem, supports model training, loading, and inference. Designed for advanced, data-driven strategies.
- **SignalPAI.mqh**: Implements a Perceptron AI-based signal generator. Inherits from `CExpertSignalAIBase`. Provides methods for initializing, training, and using a perceptron neural network for trade signal generation. Supports dynamic configuration, indicator integration, and modular AI/ML pipeline features. Designed for advanced, data-driven strategies and easy integration into the EA's AI subsystem.

### Traditional Indicator-Based Signals
- **SignalMA.mqh**: Moving Average signal generator.
- **SignalMACD.mqh**: MACD oscillator signal generator.
- **SignalRSI.mqh**: Relative Strength Index signal generator.
- **SignalStoch.mqh**: Stochastic oscillator signal generator.
- **SignalPB.mqh**: Pin Bar pattern signal generator.
- **SignalNewsFilter.mqh**: News event filter for signals, configurable by impact and lookback period.
- **SignalSessionFilter.mqh**: Session-based filter (London, New York, Tokyo sessions).

## Individual Signal Modules

Below is a comprehensive list of all signal modules in the Signals/ directory, with a brief description of each:

- **SignalAC.mqh**: (Removed)
- **SignalAO.mqh**: (Removed)
- **SignalCCI.mqh**: (Removed)
- **SignalCONV.mqh**: Convolutional AI signal. Uses a neural network for advanced pattern recognition.
- **SignalDTDB.mqh**: (Removed)
- **SignalEB.mqh**: (Removed)
- **SignalIB.mqh**: (Removed)
- **SignalITF.mqh**: Intraday Time Filter. Filters signals based on time-of-day and day-of-week.
- **SignalLSTM.mqh**: LSTM AI signal. Uses a recurrent neural network for sequence-based prediction.
- **SignalMA.mqh**: (Removed)
- **SignalMACD.mqh**: (Removed)
- **SignalNewsFilter.mqh**: (Filters trading signals based on economic news events and impact levels. Configurable lookback window and impact threshold.)
- **SignalPAI.mqh**: Implements a Perceptron AI-based signal generator. Inherits from `CExpertSignalAIBase`. Provides methods for initializing, training, and using a perceptron neural network for trade signal generation. Supports dynamic configuration, indicator integration, and modular AI/ML pipeline features. Designed for advanced, data-driven strategies and easy integration into the EA's AI subsystem.
- **SignalPB.mqh**: (Removed)
- **SignalRSI.mqh**: (Removed)
- **SignalRVI.mqh**: (Removed)
- **Signals.mqh**: Main orchestration file for all signals.
- **SignalSAR.mqh**: (Removed)
- **SignalSessionFilter.mqh**: (Removed)
- **SignalStoch.mqh**: (Removed)
- **SignalWPR.mqh**: (Removed)

## Integration Notes
- All signals derive from a common base (typically `CExpertSignalCustom` or `CExpertSignalAIBase`).
- Modular design allows for easy addition/removal of signals and filters.
- Migration to a fully AI/ML-driven pipeline is recommended for future-proofing and improved performance.
- Some files (e.g., SignalPAI.mqh) may require conversion or external review due to non-text format.

---
*Documented April 2026. For AI/ML migration and modernization, see AI_NETWORK.md and project roadmap.*
feat: Enhance README and documentation for Warrior_EA project - Updated README.md with project overview, key features, directory structure, getting started guide, and modernization roadmap. - Added AI_NETWORK.md detailing the neural network and AI/ML infrastructure, including architecture, components, usage patterns, and next steps. - Introduced DATABASE.md for the Database module, outlining key components, design highlights, usage patterns, and future enhancements. - Created README.md files for Enumerations, Expert, Money, Signals, Structures, System, Trailing, Variables directories, detailing their purpose, key components, and integration notes. - Documented the Signals subsystem, emphasizing modularity, extensibility, and AI/ML readiness. - Added comprehensive descriptions for individual signal modules in Signals/ directory. - Established clear integration notes and recommendations for future improvements across all modules. 2026-04-20 19:28:34 -04:00			`# Signals Subsystem (Signals/)`

			`## Overview`
			`The Signals/ directory contains all trade signal generation logic for the Warrior EA. It includes both traditional indicator-based signals and advanced AI/ML-driven signals. Each signal is encapsulated in its own class, supporting modularity and extensibility.`

			`## Key Components`

			`### Signals.mqh`
			`- Main orchestration file for signal modules.`
			`- Includes both traditional and AI/ML signal classes.`
			`- Facilitates integration of filters (news, session, etc.) and advanced signals.`

			`### AI/ML-Driven Signals`
			`- SignalLSTM.mqh: Implements an LSTM-based neural network signal generator. Integrates with the AI subsystem, supports model training, loading, and inference. Designed for advanced, data-driven strategies.`
			- SignalPAI.mqh: Implements a Perceptron AI-based signal generator. Inherits from `CExpertSignalAIBase`. Provides methods for initializing, training, and using a perceptron neural network for trade signal generation. Supports dynamic configuration, indicator integration, and modular AI/ML pipeline features. Designed for advanced, data-driven strategies and easy integration into the EA's AI subsystem.

			`### Traditional Indicator-Based Signals`
			`- SignalMA.mqh: Moving Average signal generator.`
			`- SignalMACD.mqh: MACD oscillator signal generator.`
			`- SignalRSI.mqh: Relative Strength Index signal generator.`
			`- SignalStoch.mqh: Stochastic oscillator signal generator.`
			`- SignalPB.mqh: Pin Bar pattern signal generator.`
			`- SignalNewsFilter.mqh: News event filter for signals, configurable by impact and lookback period.`
			`- SignalSessionFilter.mqh: Session-based filter (London, New York, Tokyo sessions).`

			`## Individual Signal Modules`

			`Below is a comprehensive list of all signal modules in the Signals/ directory, with a brief description of each:`

2026-04-20 22:35:14 -04:00			`- SignalAC.mqh: (Removed)`
			`- SignalAO.mqh: (Removed)`
			`- SignalCCI.mqh: (Removed)`
feat: Enhance README and documentation for Warrior_EA project - Updated README.md with project overview, key features, directory structure, getting started guide, and modernization roadmap. - Added AI_NETWORK.md detailing the neural network and AI/ML infrastructure, including architecture, components, usage patterns, and next steps. - Introduced DATABASE.md for the Database module, outlining key components, design highlights, usage patterns, and future enhancements. - Created README.md files for Enumerations, Expert, Money, Signals, Structures, System, Trailing, Variables directories, detailing their purpose, key components, and integration notes. - Documented the Signals subsystem, emphasizing modularity, extensibility, and AI/ML readiness. - Added comprehensive descriptions for individual signal modules in Signals/ directory. - Established clear integration notes and recommendations for future improvements across all modules. 2026-04-20 19:28:34 -04:00			`- SignalCONV.mqh: Convolutional AI signal. Uses a neural network for advanced pattern recognition.`
2026-04-20 22:35:14 -04:00			`- SignalDTDB.mqh: (Removed)`
			`- SignalEB.mqh: (Removed)`
			`- SignalIB.mqh: (Removed)`
feat: Enhance README and documentation for Warrior_EA project - Updated README.md with project overview, key features, directory structure, getting started guide, and modernization roadmap. - Added AI_NETWORK.md detailing the neural network and AI/ML infrastructure, including architecture, components, usage patterns, and next steps. - Introduced DATABASE.md for the Database module, outlining key components, design highlights, usage patterns, and future enhancements. - Created README.md files for Enumerations, Expert, Money, Signals, Structures, System, Trailing, Variables directories, detailing their purpose, key components, and integration notes. - Documented the Signals subsystem, emphasizing modularity, extensibility, and AI/ML readiness. - Added comprehensive descriptions for individual signal modules in Signals/ directory. - Established clear integration notes and recommendations for future improvements across all modules. 2026-04-20 19:28:34 -04:00			`- SignalITF.mqh: Intraday Time Filter. Filters signals based on time-of-day and day-of-week.`
			`- SignalLSTM.mqh: LSTM AI signal. Uses a recurrent neural network for sequence-based prediction.`
2026-04-20 22:35:14 -04:00			`- SignalMA.mqh: (Removed)`
			`- SignalMACD.mqh: (Removed)`
			`- SignalNewsFilter.mqh: (Filters trading signals based on economic news events and impact levels. Configurable lookback window and impact threshold.)`
feat: Enhance README and documentation for Warrior_EA project - Updated README.md with project overview, key features, directory structure, getting started guide, and modernization roadmap. - Added AI_NETWORK.md detailing the neural network and AI/ML infrastructure, including architecture, components, usage patterns, and next steps. - Introduced DATABASE.md for the Database module, outlining key components, design highlights, usage patterns, and future enhancements. - Created README.md files for Enumerations, Expert, Money, Signals, Structures, System, Trailing, Variables directories, detailing their purpose, key components, and integration notes. - Documented the Signals subsystem, emphasizing modularity, extensibility, and AI/ML readiness. - Added comprehensive descriptions for individual signal modules in Signals/ directory. - Established clear integration notes and recommendations for future improvements across all modules. 2026-04-20 19:28:34 -04:00			- SignalPAI.mqh: Implements a Perceptron AI-based signal generator. Inherits from `CExpertSignalAIBase`. Provides methods for initializing, training, and using a perceptron neural network for trade signal generation. Supports dynamic configuration, indicator integration, and modular AI/ML pipeline features. Designed for advanced, data-driven strategies and easy integration into the EA's AI subsystem.
2026-04-20 22:35:14 -04:00			`- SignalPB.mqh: (Removed)`
			`- SignalRSI.mqh: (Removed)`
			`- SignalRVI.mqh: (Removed)`
feat: Enhance README and documentation for Warrior_EA project - Updated README.md with project overview, key features, directory structure, getting started guide, and modernization roadmap. - Added AI_NETWORK.md detailing the neural network and AI/ML infrastructure, including architecture, components, usage patterns, and next steps. - Introduced DATABASE.md for the Database module, outlining key components, design highlights, usage patterns, and future enhancements. - Created README.md files for Enumerations, Expert, Money, Signals, Structures, System, Trailing, Variables directories, detailing their purpose, key components, and integration notes. - Documented the Signals subsystem, emphasizing modularity, extensibility, and AI/ML readiness. - Added comprehensive descriptions for individual signal modules in Signals/ directory. - Established clear integration notes and recommendations for future improvements across all modules. 2026-04-20 19:28:34 -04:00			`- Signals.mqh: Main orchestration file for all signals.`
2026-04-20 22:35:14 -04:00			`- SignalSAR.mqh: (Removed)`
			`- SignalSessionFilter.mqh: (Removed)`
			`- SignalStoch.mqh: (Removed)`
			`- SignalWPR.mqh: (Removed)`
feat: Enhance README and documentation for Warrior_EA project - Updated README.md with project overview, key features, directory structure, getting started guide, and modernization roadmap. - Added AI_NETWORK.md detailing the neural network and AI/ML infrastructure, including architecture, components, usage patterns, and next steps. - Introduced DATABASE.md for the Database module, outlining key components, design highlights, usage patterns, and future enhancements. - Created README.md files for Enumerations, Expert, Money, Signals, Structures, System, Trailing, Variables directories, detailing their purpose, key components, and integration notes. - Documented the Signals subsystem, emphasizing modularity, extensibility, and AI/ML readiness. - Added comprehensive descriptions for individual signal modules in Signals/ directory. - Established clear integration notes and recommendations for future improvements across all modules. 2026-04-20 19:28:34 -04:00
			`## Integration Notes`
			- All signals derive from a common base (typically `CExpertSignalCustom` or `CExpertSignalAIBase`).
			`- Modular design allows for easy addition/removal of signals and filters.`
			`- Migration to a fully AI/ML-driven pipeline is recommended for future-proofing and improved performance.`
			`- Some files (e.g., SignalPAI.mqh) may require conversion or external review due to non-text format.`

			`---`
			`Documented April 2026. For AI/ML migration and modernization, see AI_NETWORK.md and project roadmap.`