Fixing np.logical_and/or problems in Connection ProcessModels

[gkarray]

Issue Number: #411

Objective of pull request: Fixing incorrect use of np.logical_and and np.logical_or was discovered in learning-related code in Connection ProcessModels.

Pull request checklist

Your PR fulfills the following requirements:

• Issue created that explains the change and why it's needed
• Tests are part of the PR (for bug fixes / features)
• Docs reviewed and added / updated if needed (for bug fixes / features)
• PR conforms to Coding Conventions
• PR applys BSD 3-clause or LGPL2.1+ Licenses to all code files
• Lint (flakeheaven lint src/lava tests/) and (bandit -r src/lava/.) pass locally
• Build tests (pytest) passes locally

Pull request type

Please check your PR type:

• Bugfix
• Feature
• Code style update (formatting, renaming)
• Refactoring (no functional changes, no api changes)
• Build related changes
• Documentation changes
• Other (please describe):

What is the current behavior?

• Currently, to implement and and or element-wise operations on 3 np.ndarray (example : a, b and c), the following is used :
  np.logical_and(a, b, c)

What is the new behavior?

• Replaced it with :
  a & b & c

Does this introduce a breaking change?

• Yes
• No

[PhilippPlank]

This should work and is faster and as long as the arrays are only boolean it is the same behavior.