Tanh vs Tan Inverse: Which is Better?
Both Tanh (Hyperbolic Tangent) and Tan⁻¹ (Inverse Tangent / Arctan) are mathematical functions used in different contexts. They have distinct properties and applications.
1️⃣ Tanh (Hyperbolic Tangent)
- Formula: tanh(x)=ex−e−xex+e−x\tanh(x) = \frac{e^x – e^{-x}}{e^x + e^{-x}}tanh(x)=ex+e−xex−e−x
- Range: (-1, 1)
- Behavior:
- Maps large negative values close to -1 and large positive values close to 1.
- Smooth and differentiable everywhere.
- Used as an activation function in neural networks.
- Derivative: ddxtanh(x)=1−tanh2(x)\frac{d}{dx} \tanh(x) = 1 – \tanh^2(x)dxdtanh(x)=1−tanh2(x)
- Applications:
✅ Commonly used in machine learning as an activation function.
✅ Used in signal processing and hyperbolic geometry.
Example in Python (Tanh)
import numpy as np
x = np.array([-2, -1, 0, 1, 2])
tanh_output = np.tanh(x)
print(tanh_output) # [-0.9640 -0.7616 0.0000 0.7616 0.9640]
2️⃣ Tan⁻¹ (Inverse Tangent / Arctan)
- Formula: tan−1(x)=arctan(x)\tan^{-1}(x) = \arctan(x)tan−1(x)=arctan(x)
- Range: (-π/2, π/2) ≈ (-1.57, 1.57)
- Behavior:
- Maps large negative values close to -π/2 and large positive values close to π/2.
- Grows more slowly than Tanh, without a strict upper or lower bound of -1 and 1.
- Used to determine angles in trigonometry.
- Derivative: ddxtan−1(x)=11+x2\frac{d}{dx} \tan^{-1}(x) = \frac{1}{1 + x^2}dxdtan−1(x)=1+x21
- Applications:
✅ Used in trigonometry and geometry.
✅ Appears in control systems, physics, and signal processing.
Example in Python (Arctan)
arctan_output = np.arctan(x)
print(arctan_output) # [-1.107 -0.785 0.000 0.785 1.107]
🔑 Key Differences
Feature | Tanh | Tan⁻¹ (Arctan) |
---|---|---|
Formula | ex−e−xex+e−x\frac{e^x – e^{-x}}{e^x + e^{-x}}ex+e−xex−e−x | tan−1(x)\tan^{-1}(x)tan−1(x) |
Range | (-1, 1) | (-π/2, π/2) ≈ (-1.57, 1.57) |
Growth Rate | Steep | Slower |
Derivative | 1−tanh2(x)1 – \tanh^2(x)1−tanh2(x) | 11+x2\frac{1}{1 + x^2}1+x21 |
Best for | Neural networks (activation function) | Trigonometry, angle calculations |
Asymptotes | Yes, at -1 and 1 | Yes, at -π/2 and π/2 |
🛠️ When to Use Each?
- Use Tanh when working with machine learning models or when you need a bounded, smooth function between -1 and 1.
- Use Arctan when dealing with trigonometry, angles, and geometric computations.
🚀 Which is Better?
- For deep learning: Tanh is better.
- For mathematical and trigonometric calculations: Arctan is better.
Let me know if you need further details! 🚀