# embedded-dsp
[](https://crates.io/crates/embedded-dsp)
[](https://docs.rs/embedded-dsp)
[](https://github.com/leftger/embedded-dsp/actions/workflows/ci.yml)
[](LICENSE-MIT)
A **`#![no_std]` Rust Digital Signal Processing library** designed for microcontrollers (Cortex-M, RISC-V, AVR, Xtensa), embedded systems, and real-time digital signal processing applications.
---
## Features
- **`#![no_std]` First**: Pure `core` compatibility for bare-metal targets with zero dynamic allocation required.
- **`libm` Integration**: Unified `FloatMath` trait providing floating-point math routines in `#![no_std]` environments via `libm`.
- **Fixed-Point & Floating-Point**: Complete support for `f32`, `f64`, `q31`, `q15`, `q7`, and `q63` saturating arithmetic.
- **16 Core DSP Modules**:
1. **Basic Math**: Elementwise `add`, `sub`, `mult`, `negate`, `offset`, `scale`, `shift`, `dot_prod`, `clip`, bitwise operations.
2. **Complex Math**: Complex vector addition, multiplication, magnitude, conjugate, dot product.
3. **Fast Math**: Trigonometric `sin`, `cos`, `sin_cos`, `sqrt`, `vsqrt`, `divide`, `log`, `exp`, `atan2`.
4. **Filtering**: FIR filters, Biquad IIR cascade, LMS adaptive filters, 1D convolution & correlation.
5. **Transforms**: In-place Complex FFT (`cfft`), Real FFT (`rfft`), Discrete Cosine Transform (`dct4`).
6. **Matrix Operations**: Matrix addition, subtraction, multiplication, scaling, transpose, Gauss-Jordan inversion.
7. **Controller**: PID motor controller, Clarke and Park transforms.
8. **Statistics**: Mean, variance, standard deviation, RMS, power, min/max, entropy, KL divergence, logsumexp.
9. **Support & Conversions**: Array copy/fill, zero-allocation sorting (`sort_f32`), format conversions (`q15` ↔ `f32` ↔ `q31`).
10. **Interpolation**: Linear, Bilinear, and Cubic Spline interpolation.
11. **Quaternions**: Norm, normalization, quaternion product, conjugate, inverse, rotation matrix conversion.
12. **Window Functions**: Hanning, Hamming, Blackman, Bartlett, Welch, Flat-top generators.
13. **Distance Metrics**: Euclidean, Cosine, Chebyshev, Manhattan, Minkowski, Jaccard, Hamming, Canberra, Bray-Curtis.
14. **Machine Learning**: Support Vector Machine (`SvmInstanceF32`) and Gaussian Naive Bayes (`GaussianNaiveBayesInstanceF32`).
---
## Quick Start
Add `embedded-dsp` to your `Cargo.toml`:
```toml
[dependencies]
# For bare-metal #![no_std] environments with libm
embedded-dsp = { version = "0.1", default-features = false, features = ["libm"] }
# For standard std environments
embedded-dsp = "0.1"
```
### Basic Example
```rust
use embedded_dsp::*;
fn main() {
// 1. Vector Operations
let a = [1.0f32, 2.0, 3.0, 4.0];
let b = [10.0f32, 20.0, 30.0, 40.0];
let mut vec_out = [0.0f32; 4];
add_f32(&a, &b, &mut vec_out);
// 2. Q15 Fixed-Point Saturating Addition
let q15_a = [20000i16, 25000];
let q15_b = [15000i16, 10000];
let mut q15_out = [0i16; 2];
add_q15(&q15_a, &q15_b, &mut q15_out); // Output: [32767, 32767] (clamped at i16::MAX)
// 3. 64-Point Complex FFT
let mut fft_data = [0.0f32; 128]; // 64 complex pairs [re, im, ...]
cfft_f32(&mut fft_data, 64, 0, 1);
}
```
---
## Running Included Examples
```bash
# Run basic usage example
cargo run --example basic_usage
# Run performance comparison benchmark (libm vs embedded-dsp)
cargo run --release --example perf_comparison
```
---
## License
The contents of this repository are dual-licensed under the _MIT OR Apache 2.0_
License. That means you can choose either the MIT license or the Apache 2.0
license when you re-use this code. See [`LICENSE`](./LICENSE), [`LICENSE-MIT`](./LICENSE-MIT), or
[`LICENSE-APACHE`](./LICENSE-APACHE) for more information on each specific
license.